Overview

Dataset statistics

Number of variables104
Number of observations88284
Missing cells530212
Missing cells (%)5.8%
Total size in memory70.7 MiB
Average record size in memory840.0 B

Variable types

Numeric99
Text5

Alerts

age has 4055 (4.6%) missing valuesMissing
ethnicity has 1211 (1.4%) missing valuesMissing
apache_2_diagnosis has 1566 (1.8%) missing valuesMissing
apache_3j_diagnosis has 1026 (1.2%) missing valuesMissing
bun_apache has 18289 (20.7%) missing valuesMissing
creatinine_apache has 17926 (20.3%) missing valuesMissing
gcs_eyes_apache has 1794 (2.0%) missing valuesMissing
gcs_motor_apache has 1794 (2.0%) missing valuesMissing
gcs_unable_apache has 951 (1.1%) missing valuesMissing
gcs_verbal_apache has 1794 (2.0%) missing valuesMissing
glucose_apache has 10473 (11.9%) missing valuesMissing
hematocrit_apache has 19005 (21.5%) missing valuesMissing
map_apache has 913 (1.0%) missing valuesMissing
resprate_apache has 1131 (1.3%) missing valuesMissing
sodium_apache has 17644 (20.0%) missing valuesMissing
temp_apache has 3884 (4.4%) missing valuesMissing
wbc_apache has 21063 (23.9%) missing valuesMissing
d1_diasbp_noninvasive_max has 959 (1.1%) missing valuesMissing
d1_diasbp_noninvasive_min has 959 (1.1%) missing valuesMissing
d1_mbp_noninvasive_max has 1333 (1.5%) missing valuesMissing
d1_mbp_noninvasive_min has 1333 (1.5%) missing valuesMissing
d1_sysbp_noninvasive_max has 946 (1.1%) missing valuesMissing
d1_sysbp_noninvasive_min has 946 (1.1%) missing valuesMissing
d1_temp_max has 2205 (2.5%) missing valuesMissing
d1_temp_min has 2205 (2.5%) missing valuesMissing
h1_diasbp_max has 3388 (3.8%) missing valuesMissing
h1_diasbp_min has 3388 (3.8%) missing valuesMissing
h1_diasbp_noninvasive_max has 6982 (7.9%) missing valuesMissing
h1_diasbp_noninvasive_min has 6982 (7.9%) missing valuesMissing
h1_heartrate_max has 2621 (3.0%) missing valuesMissing
h1_heartrate_min has 2621 (3.0%) missing valuesMissing
h1_mbp_max has 4287 (4.9%) missing valuesMissing
h1_mbp_min has 4287 (4.9%) missing valuesMissing
h1_mbp_noninvasive_max has 8455 (9.6%) missing valuesMissing
h1_mbp_noninvasive_min has 8455 (9.6%) missing valuesMissing
h1_resprate_max has 4062 (4.6%) missing valuesMissing
h1_resprate_min has 4062 (4.6%) missing valuesMissing
h1_spo2_max has 3925 (4.4%) missing valuesMissing
h1_spo2_min has 3925 (4.4%) missing valuesMissing
h1_sysbp_max has 3379 (3.8%) missing valuesMissing
h1_sysbp_min has 3379 (3.8%) missing valuesMissing
h1_sysbp_noninvasive_max has 6972 (7.9%) missing valuesMissing
h1_sysbp_noninvasive_min has 6972 (7.9%) missing valuesMissing
h1_temp_max has 20833 (23.6%) missing valuesMissing
h1_temp_min has 20833 (23.6%) missing valuesMissing
d1_bun_max has 9860 (11.2%) missing valuesMissing
d1_bun_min has 9860 (11.2%) missing valuesMissing
d1_calcium_max has 12315 (13.9%) missing valuesMissing
d1_calcium_min has 12315 (13.9%) missing valuesMissing
d1_creatinine_max has 9561 (10.8%) missing valuesMissing
d1_creatinine_min has 9561 (10.8%) missing valuesMissing
d1_glucose_max has 5458 (6.2%) missing valuesMissing
d1_glucose_min has 5458 (6.2%) missing valuesMissing
d1_hco3_max has 14390 (16.3%) missing valuesMissing
d1_hco3_min has 14390 (16.3%) missing valuesMissing
d1_hemaglobin_max has 11519 (13.0%) missing valuesMissing
d1_hemaglobin_min has 11519 (13.0%) missing valuesMissing
d1_hematocrit_max has 11051 (12.5%) missing valuesMissing
d1_hematocrit_min has 11051 (12.5%) missing valuesMissing
d1_platelets_max has 12767 (14.5%) missing valuesMissing
d1_platelets_min has 12767 (14.5%) missing valuesMissing
d1_potassium_max has 9053 (10.3%) missing valuesMissing
d1_potassium_min has 9053 (10.3%) missing valuesMissing
d1_sodium_max has 9554 (10.8%) missing valuesMissing
d1_sodium_min has 9554 (10.8%) missing valuesMissing
d1_wbc_max has 12501 (14.2%) missing valuesMissing
d1_wbc_min has 12501 (14.2%) missing valuesMissing
apache_4a_hospital_death_prob has 7594 (8.6%) missing valuesMissing
apache_4a_icu_death_prob has 7594 (8.6%) missing valuesMissing
apache_3j_bodysystem has 1566 (1.8%) missing valuesMissing
apache_2_bodysystem has 1566 (1.8%) missing valuesMissing
aids is highly skewed (γ1 = 33.90681081)Skewed
hospital_death has 80732 (91.4%) zerosZeros
elective_surgery has 71999 (81.6%) zerosZeros
pre_icu_los_days has 3480 (3.9%) zerosZeros
apache_post_operative has 70458 (79.8%) zerosZeros
arf_apache has 85144 (96.4%) zerosZeros
gcs_unable_apache has 86490 (98.0%) zerosZeros
intubated_apache has 74275 (84.1%) zerosZeros
ventilated_apache has 58942 (66.8%) zerosZeros
d1_resprate_min has 3486 (3.9%) zerosZeros
apache_4a_hospital_death_prob has 2352 (2.7%) zerosZeros
apache_4a_icu_death_prob has 9258 (10.5%) zerosZeros
aids has 87524 (99.1%) zerosZeros
cirrhosis has 86221 (97.7%) zerosZeros
diabetes_mellitus has 67861 (76.9%) zerosZeros
hepatic_failure has 86455 (97.9%) zerosZeros
immunosuppression has 85316 (96.6%) zerosZeros
leukemia has 86976 (98.5%) zerosZeros
lymphoma has 87230 (98.8%) zerosZeros
solid_tumor_with_metastasis has 85795 (97.2%) zerosZeros

Reproduction

Analysis started2023-10-06 11:48:08.709076
Analysis finished2023-10-06 11:48:13.502059
Duration4.79 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

hospital_death
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08554211409
Minimum0
Maximum1
Zeros80732
Zeros (%)91.4%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:13.850226image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2796883031
Coefficient of variation (CV)3.269597742
Kurtosis6.784144555
Mean0.08554211409
Median Absolute Deviation (MAD)0
Skewness2.963779828
Sum7552
Variance0.07822554687
MonotonicityNot monotonic
2023-10-06T17:18:13.998532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 80732
91.4%
1 7552
 
8.6%
ValueCountFrequency (%)
0 80732
91.4%
1 7552
 
8.6%
ValueCountFrequency (%)
1 7552
 
8.6%
0 80732
91.4%

age
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)0.1%
Missing4055
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean62.34199622
Minimum16
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:14.174364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile29
Q152
median65
Q375
95-th percentile86
Maximum89
Range73
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.75179681
Coefficient of variation (CV)0.2687080591
Kurtosis-0.2044609226
Mean62.34199622
Median Absolute Deviation (MAD)11
Skewness-0.6254972942
Sum5251004
Variance280.6226962
MonotonicityNot monotonic
2023-10-06T17:18:14.304787image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67 2198
 
2.5%
68 2113
 
2.4%
71 2054
 
2.3%
72 2044
 
2.3%
66 1983
 
2.2%
65 1980
 
2.2%
70 1948
 
2.2%
63 1908
 
2.2%
73 1900
 
2.2%
69 1875
 
2.1%
Other values (64) 64226
72.7%
(Missing) 4055
 
4.6%
ValueCountFrequency (%)
16 41
 
< 0.1%
17 121
 
0.1%
18 240
0.3%
19 328
0.4%
20 329
0.4%
ValueCountFrequency (%)
89 928
1.1%
88 998
1.1%
87 1165
1.3%
86 1258
1.4%
85 1366
1.5%

bmi
Real number (ℝ)

Distinct34888
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.18581767
Minimum14.84492591
Maximum67.81498973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:14.452811image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14.84492591
5-th percentile18.855359
Q123.64197531
median27.65465458
Q332.93020569
95-th percentile44.51653785
Maximum67.81498973
Range52.97006382
Interquartile range (IQR)9.288230385

Descriptive statistics

Standard deviation8.275142229
Coefficient of variation (CV)0.2835329927
Kurtosis3.411489377
Mean29.18581767
Median Absolute Deviation (MAD)4.50969667
Skewness1.440832975
Sum2576640.727
Variance68.47797891
MonotonicityNot monotonic
2023-10-06T17:18:14.675336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.84492591 443
 
0.5%
67.81498973 422
 
0.5%
24.01776785 87
 
0.1%
24.20811 86
 
0.1%
27.35933163 82
 
0.1%
24.8046875 79
 
0.1%
22.60610272 79
 
0.1%
23.29590458 79
 
0.1%
25.81229652 77
 
0.1%
29.049732 76
 
0.1%
Other values (34878) 86774
98.3%
ValueCountFrequency (%)
14.84492591 443
0.5%
14.84526746 1
 
< 0.1%
14.86419531 1
 
< 0.1%
14.86453979 2
 
< 0.1%
14.86695021 1
 
< 0.1%
ValueCountFrequency (%)
67.81498973 422
0.5%
67.81263563 1
 
< 0.1%
67.7978059 1
 
< 0.1%
67.78345128 1
 
< 0.1%
67.77927558 1
 
< 0.1%

elective_surgery
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1844615106
Minimum0
Maximum1
Zeros71999
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:14.956282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3878623025
Coefficient of variation (CV)2.102673351
Kurtosis0.6474734677
Mean0.1844615106
Median Absolute Deviation (MAD)0
Skewness1.627101349
Sum16285
Variance0.1504371657
MonotonicityNot monotonic
2023-10-06T17:18:15.100259image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 71999
81.6%
1 16285
 
18.4%
ValueCountFrequency (%)
0 71999
81.6%
1 16285
 
18.4%
ValueCountFrequency (%)
1 16285
 
18.4%
0 71999
81.6%

ethnicity
Text

MISSING 

Distinct6
Distinct (%)< 0.1%
Missing1211
Missing (%)1.4%
Memory size1.3 MiB
2023-10-06T17:18:15.268684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length9
Mean length9.900485799
Min length5

Characters and Unicode

Total characters862065
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCaucasian
2nd rowCaucasian
3rd rowCaucasian
4th rowCaucasian
5th rowCaucasian
ValueCountFrequency (%)
caucasian 68091
70.1%
american 10005
 
10.3%
african 9239
 
9.5%
other/unknown 4279
 
4.4%
hispanic 3605
 
3.7%
asian 1093
 
1.1%
native 766
 
0.8%
2023-10-06T17:18:15.672724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 228981
26.6%
n 104870
12.2%
i 96404
11.2%
c 90940
 
10.5%
s 72789
 
8.4%
C 68091
 
7.9%
u 68091
 
7.9%
r 23523
 
2.7%
A 20337
 
2.4%
e 15050
 
1.7%
Other values (15) 72989
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 746424
86.6%
Uppercase Letter 101357
 
11.8%
Space Separator 10005
 
1.2%
Other Punctuation 4279
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 228981
30.7%
n 104870
14.0%
i 96404
12.9%
c 90940
 
12.2%
s 72789
 
9.8%
u 68091
 
9.1%
r 23523
 
3.2%
e 15050
 
2.0%
m 10005
 
1.3%
f 9239
 
1.2%
Other values (7) 26532
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
C 68091
67.2%
A 20337
 
20.1%
O 4279
 
4.2%
U 4279
 
4.2%
H 3605
 
3.6%
N 766
 
0.8%
Space Separator
ValueCountFrequency (%)
10005
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 847781
98.3%
Common 14284
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 228981
27.0%
n 104870
12.4%
i 96404
11.4%
c 90940
 
10.7%
s 72789
 
8.6%
C 68091
 
8.0%
u 68091
 
8.0%
r 23523
 
2.8%
A 20337
 
2.4%
e 15050
 
1.8%
Other values (13) 58705
 
6.9%
Common
ValueCountFrequency (%)
10005
70.0%
/ 4279
30.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 862065
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 228981
26.6%
n 104870
12.2%
i 96404
11.2%
c 90940
 
10.5%
s 72789
 
8.4%
C 68091
 
7.9%
u 68091
 
7.9%
r 23523
 
2.7%
A 20337
 
2.4%
e 15050
 
1.7%
Other values (15) 72989
 
8.5%

gender
Text

Distinct2
Distinct (%)< 0.1%
Missing18
Missing (%)< 0.1%
Memory size1.3 MiB
2023-10-06T17:18:15.848967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters88266
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowF
3rd rowF
4th rowF
5th rowM
ValueCountFrequency (%)
m 47632
54.0%
f 40634
46.0%
2023-10-06T17:18:16.100310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 47632
54.0%
F 40634
46.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 88266
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 47632
54.0%
F 40634
46.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 88266
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 47632
54.0%
F 40634
46.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 47632
54.0%
F 40634
46.0%

height
Real number (ℝ)

Distinct400
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169.646433
Minimum137.2
Maximum195.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:16.236190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum137.2
5-th percentile152.4
Q1162.5
median170.1
Q3177.8
95-th percentile187.9
Maximum195.59
Range58.39
Interquartile range (IQR)15.3

Descriptive statistics

Standard deviation10.79411673
Coefficient of variation (CV)0.06362713637
Kurtosis-0.3909690688
Mean169.646433
Median Absolute Deviation (MAD)7.7
Skewness-0.1004757834
Sum14977065.69
Variance116.5129559
MonotonicityNot monotonic
2023-10-06T17:18:16.432984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167.6 5205
 
5.9%
177.8 5152
 
5.8%
160 5143
 
5.8%
172.7 4660
 
5.3%
165.1 4652
 
5.3%
170.2 4001
 
4.5%
162.6 3751
 
4.2%
182.9 3540
 
4.0%
180.3 3456
 
3.9%
175.3 3412
 
3.9%
Other values (390) 45312
51.3%
ValueCountFrequency (%)
137.2 439
0.5%
137.5 1
 
< 0.1%
137.6 1
 
< 0.1%
138 4
 
< 0.1%
138.4 1
 
< 0.1%
ValueCountFrequency (%)
195.59 415
0.5%
195.58 5
 
< 0.1%
195.5 29
 
< 0.1%
195.3 1
 
< 0.1%
195 21
 
< 0.1%
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:16.609853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length9.673542205
Min length4

Characters and Unicode

Total characters854019
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCTICU
2nd rowMed-Surg ICU
3rd rowMed-Surg ICU
4th rowCTICU
5th rowMed-Surg ICU
ValueCountFrequency (%)
icu 60656
40.7%
med-surg 48620
32.6%
micu 7512
 
5.0%
neuro 7402
 
5.0%
ccu-cticu 6840
 
4.6%
sicu 5001
 
3.4%
cardiac 4634
 
3.1%
csicu 4569
 
3.1%
cticu 3706
 
2.5%
2023-10-06T17:18:16.919524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 121713
14.3%
U 95124
11.1%
I 88284
10.3%
r 60656
7.1%
60656
7.1%
S 58190
 
6.8%
M 56132
 
6.6%
u 56022
 
6.6%
e 56022
 
6.6%
- 55460
 
6.5%
Other values (8) 145760
17.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 437391
51.2%
Lowercase Letter 300512
35.2%
Space Separator 60656
 
7.1%
Dash Punctuation 55460
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 60656
20.2%
u 56022
18.6%
e 56022
18.6%
d 53254
17.7%
g 48620
16.2%
a 9268
 
3.1%
o 7402
 
2.5%
i 4634
 
1.5%
c 4634
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
C 121713
27.8%
U 95124
21.7%
I 88284
20.2%
S 58190
13.3%
M 56132
12.8%
T 10546
 
2.4%
N 7402
 
1.7%
Space Separator
ValueCountFrequency (%)
60656
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 737903
86.4%
Common 116116
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 121713
16.5%
U 95124
12.9%
I 88284
12.0%
r 60656
8.2%
S 58190
7.9%
M 56132
7.6%
u 56022
7.6%
e 56022
7.6%
d 53254
7.2%
g 48620
 
6.6%
Other values (6) 43886
 
5.9%
Common
ValueCountFrequency (%)
60656
52.2%
- 55460
47.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 854019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 121713
14.3%
U 95124
11.1%
I 88284
10.3%
r 60656
7.1%
60656
7.1%
S 58190
 
6.8%
M 56132
 
6.6%
u 56022
 
6.6%
e 56022
 
6.6%
- 55460
 
6.5%
Other values (8) 145760
17.1%

pre_icu_los_days
Real number (ℝ)

ZEROS 

Distinct9570
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8410220535
Minimum-24.94722222
Maximum159.0909722
Zeros3480
Zeros (%)3.9%
Negative729
Negative (%)0.8%
Memory size1.3 MiB
2023-10-06T17:18:17.067321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-24.94722222
5-th percentile0.000694444
Q10.038194444
median0.142361111
Q30.413888889
95-th percentile4.397118055
Maximum159.0909722
Range184.0381944
Interquartile range (IQR)0.375694445

Descriptive statistics

Standard deviation2.499114817
Coefficient of variation (CV)2.971521146
Kurtosis316.5127534
Mean0.8410220535
Median Absolute Deviation (MAD)0.130555555
Skewness11.08877275
Sum74248.79097
Variance6.245574867
MonotonicityNot monotonic
2023-10-06T17:18:17.266126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3480
 
3.9%
0.000694444 1228
 
1.4%
0.001388889 904
 
1.0%
0.002083333 803
 
0.9%
0.002777778 747
 
0.8%
0.003472222 711
 
0.8%
0.004861111 665
 
0.8%
0.004166667 652
 
0.7%
0.00625 615
 
0.7%
0.005555556 571
 
0.6%
Other values (9560) 77908
88.2%
ValueCountFrequency (%)
-24.94722222 1
< 0.1%
-13.775 1
< 0.1%
-11.40972222 1
< 0.1%
-10.69375 1
< 0.1%
-6.634722222 1
< 0.1%
ValueCountFrequency (%)
159.0909722 1
< 0.1%
84.36736111 1
< 0.1%
81.80277778 1
< 0.1%
78.7625 1
< 0.1%
73.02291667 1
< 0.1%

weight
Real number (ℝ)

Distinct3403
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.02069673
Minimum38.6
Maximum186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:17.435705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum38.6
5-th percentile50.3
Q166.8
median80.3
Q397.1
95-th percentile130
Maximum186
Range147.4
Interquartile range (IQR)30.3

Descriptive statistics

Standard deviation25.00721151
Coefficient of variation (CV)0.2976315656
Kurtosis1.838817703
Mean84.02069673
Median Absolute Deviation (MAD)14.9
Skewness1.068356652
Sum7417683.19
Variance625.3606276
MonotonicityNot monotonic
2023-10-06T17:18:17.614578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 972
 
1.1%
81.6 884
 
1.0%
63.5 839
 
1.0%
90.7 774
 
0.9%
77.1 731
 
0.8%
75 557
 
0.6%
72.6 554
 
0.6%
59 539
 
0.6%
80 507
 
0.6%
83.9 501
 
0.6%
Other values (3393) 81426
92.2%
ValueCountFrequency (%)
38.6 456
0.5%
38.7 5
 
< 0.1%
38.8 6
 
< 0.1%
38.9 4
 
< 0.1%
39 33
 
< 0.1%
ValueCountFrequency (%)
186 440
0.5%
185.8 1
 
< 0.1%
185.6 1
 
< 0.1%
185.5 4
 
< 0.1%
185.4 1
 
< 0.1%

apache_2_diagnosis
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)0.1%
Missing1566
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean185.4734542
Minimum101
Maximum308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:17.870326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile106
Q1113
median122
Q3301
95-th percentile307
Maximum308
Range207
Interquartile range (IQR)188

Descriptive statistics

Standard deviation86.06309773
Coefficient of variation (CV)0.4640184123
Kurtosis-1.586860261
Mean185.4734542
Median Absolute Deviation (MAD)16
Skewness0.5056215985
Sum16083887
Variance7406.856792
MonotonicityNot monotonic
2023-10-06T17:18:18.032677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
113 11368
 
12.9%
301 6528
 
7.4%
302 6424
 
7.3%
112 4147
 
4.7%
308 3995
 
4.5%
124 3772
 
4.3%
117 3758
 
4.3%
122 3553
 
4.0%
303 3231
 
3.7%
110 3095
 
3.5%
Other values (34) 36847
41.7%
ValueCountFrequency (%)
101 361
 
0.4%
102 1815
2.1%
103 282
 
0.3%
104 351
 
0.4%
105 1000
1.1%
ValueCountFrequency (%)
308 3995
4.5%
307 1776
2.0%
306 621
 
0.7%
305 2185
2.5%
304 2979
3.4%

apache_3j_diagnosis
Real number (ℝ)

MISSING 

Distinct398
Distinct (%)0.5%
Missing1026
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean559.0233058
Minimum0.01
Maximum2201.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:18.220804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile104.01
Q1203.01
median409.02
Q3703.03
95-th percentile1501.01
Maximum2201.05
Range2201.04
Interquartile range (IQR)500.02

Descriptive statistics

Standard deviation463.6368492
Coefficient of variation (CV)0.8293694455
Kurtosis0.01311067603
Mean559.0233058
Median Absolute Deviation (MAD)294.01
Skewness1.011731235
Sum48779255.62
Variance214959.1279
MonotonicityNot monotonic
2023-10-06T17:18:18.435357image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
501.05 4333
 
4.9%
107.01 4147
 
4.7%
106.01 3758
 
4.3%
403.01 3647
 
4.1%
703.03 2921
 
3.3%
104.01 2860
 
3.2%
502.01 2759
 
3.1%
1207.01 2689
 
3.0%
102.01 2130
 
2.4%
702.01 2010
 
2.3%
Other values (388) 56004
63.4%
ValueCountFrequency (%)
0.01 1
 
< 0.1%
0.02 1
 
< 0.1%
0.03 1
 
< 0.1%
0.04 3
< 0.1%
0.06 1
 
< 0.1%
ValueCountFrequency (%)
2201.05 60
0.1%
2201.04 4
 
< 0.1%
2201.03 12
 
< 0.1%
2201.02 10
 
< 0.1%
2201.01 12
 
< 0.1%

apache_post_operative
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2019165421
Minimum0
Maximum1
Zeros70458
Zeros (%)79.8%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:18.581593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4014325316
Coefficient of variation (CV)1.988111165
Kurtosis0.2056226273
Mean0.2019165421
Median Absolute Deviation (MAD)0
Skewness1.485132307
Sum17826
Variance0.1611480774
MonotonicityNot monotonic
2023-10-06T17:18:18.694137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 70458
79.8%
1 17826
 
20.2%
ValueCountFrequency (%)
0 70458
79.8%
1 17826
 
20.2%
ValueCountFrequency (%)
1 17826
 
20.2%
0 70458
79.8%

arf_apache
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.02803652968
Minimum0
Maximum1
Zeros85144
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:18.803440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1650781444
Coefficient of variation (CV)5.887966389
Kurtosis30.69841835
Mean0.02803652968
Median Absolute Deviation (MAD)0
Skewness5.718191801
Sum2456
Variance0.02725079377
MonotonicityNot monotonic
2023-10-06T17:18:18.898547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 85144
96.4%
1 2456
 
2.8%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 85144
96.4%
1 2456
 
2.8%
ValueCountFrequency (%)
1 2456
 
2.8%
0 85144
96.4%

bun_apache
Real number (ℝ)

MISSING 

Distinct476
Distinct (%)0.7%
Missing18289
Missing (%)20.7%
Infinite0
Infinite (%)0.0%
Mean25.81643989
Minimum4
Maximum127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:19.050507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7
Q113
median19
Q332
95-th percentile69
Maximum127
Range123
Interquartile range (IQR)19

Descriptive statistics

Standard deviation20.64806278
Coefficient of variation (CV)0.7998028724
Kurtosis5.415915078
Mean25.81643989
Median Absolute Deviation (MAD)8
Skewness2.128717802
Sum1807021.71
Variance426.3424965
MonotonicityNot monotonic
2023-10-06T17:18:19.266271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 3080
 
3.5%
14 3057
 
3.5%
12 3020
 
3.4%
15 2989
 
3.4%
11 2916
 
3.3%
16 2756
 
3.1%
10 2721
 
3.1%
17 2511
 
2.8%
18 2350
 
2.7%
9 2270
 
2.6%
Other values (466) 42325
47.9%
(Missing) 18289
20.7%
ValueCountFrequency (%)
4 748
0.8%
4.3 2
 
< 0.1%
4.4 1
 
< 0.1%
4.6 2
 
< 0.1%
4.7 1
 
< 0.1%
ValueCountFrequency (%)
127 343
0.4%
126 16
 
< 0.1%
125 13
 
< 0.1%
124 14
 
< 0.1%
123 20
 
< 0.1%

creatinine_apache
Real number (ℝ)

MISSING 

Distinct1126
Distinct (%)1.6%
Missing17926
Missing (%)20.3%
Infinite0
Infinite (%)0.0%
Mean1.478789534
Minimum0.3
Maximum11.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:19.399218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.5
Q10.72
median0.97
Q31.53
95-th percentile4.4
Maximum11.18
Range10.88
Interquartile range (IQR)0.81

Descriptive statistics

Standard deviation1.526811976
Coefficient of variation (CV)1.032474156
Kurtosis15.0816998
Mean1.478789534
Median Absolute Deviation (MAD)0.32
Skewness3.542771968
Sum104044.674
Variance2.33115481
MonotonicityNot monotonic
2023-10-06T17:18:19.554620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 2500
 
2.8%
0.7 2484
 
2.8%
0.9 2000
 
2.3%
0.6 1868
 
2.1%
1 1282
 
1.5%
1.1 1279
 
1.4%
1.2 1130
 
1.3%
0.5 1092
 
1.2%
1.3 928
 
1.1%
1.4 767
 
0.9%
Other values (1116) 55028
62.3%
(Missing) 17926
 
20.3%
ValueCountFrequency (%)
0.3 350
0.4%
0.31 40
 
< 0.1%
0.316 2
 
< 0.1%
0.32 45
 
0.1%
0.33 43
 
< 0.1%
ValueCountFrequency (%)
11.18 334
0.4%
11.17 2
 
< 0.1%
11.11 1
 
< 0.1%
11.1 4
 
< 0.1%
11.08 1
 
< 0.1%

gcs_eyes_apache
Real number (ℝ)

MISSING 

Distinct4
Distinct (%)< 0.1%
Missing1794
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean3.462088103
Minimum1
Maximum4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:19.673630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q34
95-th percentile4
Maximum4
Range3
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.952600146
Coefficient of variation (CV)0.2751519077
Kurtosis1.489057873
Mean3.462088103
Median Absolute Deviation (MAD)0
Skewness-1.675196614
Sum299436
Variance0.9074470382
MonotonicityNot monotonic
2023-10-06T17:18:19.767534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
4 60480
68.5%
3 13475
 
15.3%
1 7979
 
9.0%
2 4556
 
5.2%
(Missing) 1794
 
2.0%
ValueCountFrequency (%)
1 7979
 
9.0%
2 4556
 
5.2%
3 13475
 
15.3%
4 60480
68.5%
ValueCountFrequency (%)
4 60480
68.5%
3 13475
 
15.3%
2 4556
 
5.2%
1 7979
 
9.0%

gcs_motor_apache
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)< 0.1%
Missing1794
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean5.469719043
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:19.866560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.288631754
Coefficient of variation (CV)0.2355937744
Kurtosis6.302896325
Mean5.469719043
Median Absolute Deviation (MAD)0
Skewness-2.707877522
Sum473076
Variance1.660571797
MonotonicityNot monotonic
2023-10-06T17:18:19.986111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 68244
77.3%
5 7738
 
8.8%
1 5339
 
6.0%
4 4370
 
4.9%
3 505
 
0.6%
2 294
 
0.3%
(Missing) 1794
 
2.0%
ValueCountFrequency (%)
1 5339
6.0%
2 294
 
0.3%
3 505
 
0.6%
4 4370
4.9%
5 7738
8.8%
ValueCountFrequency (%)
6 68244
77.3%
5 7738
 
8.8%
4 4370
 
4.9%
3 505
 
0.6%
2 294
 
0.3%

gcs_unable_apache
Real number (ℝ)

MISSING  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing951
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean0.009652708598
Minimum0
Maximum1
Zeros86490
Zeros (%)98.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:20.075589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09777342828
Coefficient of variation (CV)10.1291184
Kurtosis98.61332599
Mean0.009652708598
Median Absolute Deviation (MAD)0
Skewness10.03050685
Sum843
Variance0.009559643277
MonotonicityNot monotonic
2023-10-06T17:18:20.170725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 86490
98.0%
1 843
 
1.0%
(Missing) 951
 
1.1%
ValueCountFrequency (%)
0 86490
98.0%
1 843
 
1.0%
ValueCountFrequency (%)
1 843
 
1.0%
0 86490
98.0%

gcs_verbal_apache
Real number (ℝ)

MISSING 

Distinct5
Distinct (%)< 0.1%
Missing1794
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean3.987721124
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:20.281452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.56371374
Coefficient of variation (CV)0.3921321705
Kurtosis-0.3236810713
Mean3.987721124
Median Absolute Deviation (MAD)0
Skewness-1.192549318
Sum344898
Variance2.445200659
MonotonicityNot monotonic
2023-10-06T17:18:20.367637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
5 54610
61.9%
1 16242
 
18.4%
4 10573
 
12.0%
3 3184
 
3.6%
2 1881
 
2.1%
(Missing) 1794
 
2.0%
ValueCountFrequency (%)
1 16242
 
18.4%
2 1881
 
2.1%
3 3184
 
3.6%
4 10573
 
12.0%
5 54610
61.9%
ValueCountFrequency (%)
5 54610
61.9%
4 10573
 
12.0%
3 3184
 
3.6%
2 1881
 
2.1%
1 16242
 
18.4%

glucose_apache
Real number (ℝ)

MISSING 

Distinct565
Distinct (%)0.7%
Missing10473
Missing (%)11.9%
Infinite0
Infinite (%)0.0%
Mean160.5052679
Minimum39
Maximum598.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:20.517314image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile73
Q197
median134
Q3196
95-th percentile341
Maximum598.7
Range559.7
Interquartile range (IQR)99

Descriptive statistics

Standard deviation90.9369997
Coefficient of variation (CV)0.5665670722
Kurtosis4.413653246
Mean160.5052679
Median Absolute Deviation (MAD)43
Skewness1.839211809
Sum12489075.4
Variance8269.537915
MonotonicityNot monotonic
2023-10-06T17:18:20.672874image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 926
 
1.0%
92 914
 
1.0%
97 896
 
1.0%
91 889
 
1.0%
98 886
 
1.0%
93 876
 
1.0%
95 872
 
1.0%
99 868
 
1.0%
94 856
 
1.0%
90 830
 
0.9%
Other values (555) 68998
78.2%
(Missing) 10473
 
11.9%
ValueCountFrequency (%)
39 393
0.4%
40 30
 
< 0.1%
41 41
 
< 0.1%
42 47
 
0.1%
43 30
 
< 0.1%
ValueCountFrequency (%)
598.7 400
0.5%
598 6
 
< 0.1%
597 3
 
< 0.1%
596 2
 
< 0.1%
595 3
 
< 0.1%

heart_rate_apache
Real number (ℝ)

Distinct149
Distinct (%)0.2%
Missing809
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean99.79427265
Minimum30
Maximum178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:20.836858image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile47
Q186
median104
Q3120
95-th percentile146
Maximum178
Range148
Interquartile range (IQR)34

Descriptive statistics

Standard deviation30.84910503
Coefficient of variation (CV)0.3091270091
Kurtosis-0.4435746846
Mean99.79427265
Median Absolute Deviation (MAD)16
Skewness-0.2697731899
Sum8729504
Variance951.6672809
MonotonicityNot monotonic
2023-10-06T17:18:20.999535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 1778
 
2.0%
102 1727
 
2.0%
108 1727
 
2.0%
98 1658
 
1.9%
104 1657
 
1.9%
106 1631
 
1.8%
96 1562
 
1.8%
110 1561
 
1.8%
60 1552
 
1.8%
112 1551
 
1.8%
Other values (139) 71071
80.5%
ValueCountFrequency (%)
30 524
0.6%
31 70
 
0.1%
32 102
 
0.1%
33 78
 
0.1%
34 106
 
0.1%
ValueCountFrequency (%)
178 445
0.5%
177 33
 
< 0.1%
176 37
 
< 0.1%
175 45
 
0.1%
174 55
 
0.1%

hematocrit_apache
Real number (ℝ)

MISSING 

Distinct353
Distinct (%)0.5%
Missing19005
Missing (%)21.5%
Infinite0
Infinite (%)0.0%
Mean32.95600543
Minimum16.2
Maximum51.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:21.172065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum16.2
5-th percentile21.6
Q128
median33.1
Q337.9
95-th percentile43.8
Maximum51.4
Range35.2
Interquartile range (IQR)9.9

Descriptive statistics

Standard deviation6.87219917
Coefficient of variation (CV)0.2085264607
Kurtosis-0.363775495
Mean32.95600543
Median Absolute Deviation (MAD)4.9
Skewness0.001075101916
Sum2283159.1
Variance47.22712144
MonotonicityNot monotonic
2023-10-06T17:18:21.385299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 533
 
0.6%
36 527
 
0.6%
35 505
 
0.6%
33 489
 
0.6%
31 475
 
0.5%
29 468
 
0.5%
32 456
 
0.5%
37 445
 
0.5%
30 443
 
0.5%
38 436
 
0.5%
Other values (343) 64502
73.1%
(Missing) 19005
 
21.5%
ValueCountFrequency (%)
16.2 364
0.4%
16.3 18
 
< 0.1%
16.4 19
 
< 0.1%
16.5 20
 
< 0.1%
16.6 8
 
< 0.1%
ValueCountFrequency (%)
51.4 348
0.4%
51.3 17
 
< 0.1%
51.2 9
 
< 0.1%
51.1 11
 
< 0.1%
51 16
 
< 0.1%

intubated_apache
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.1521118721
Minimum0
Maximum1
Zeros74275
Zeros (%)84.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:21.755049image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3591313448
Coefficient of variation (CV)2.360968541
Kurtosis1.75367828
Mean0.1521118721
Median Absolute Deviation (MAD)0
Skewness1.937430835
Sum13325
Variance0.1289753228
MonotonicityNot monotonic
2023-10-06T17:18:22.094126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 74275
84.1%
1 13325
 
15.1%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 74275
84.1%
1 13325
 
15.1%
ValueCountFrequency (%)
1 13325
 
15.1%
0 74275
84.1%

map_apache
Real number (ℝ)

MISSING 

Distinct161
Distinct (%)0.2%
Missing913
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean87.9472365
Minimum40
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:22.500620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile42
Q154
median66
Q3125
95-th percentile164
Maximum200
Range160
Interquartile range (IQR)71

Descriptive statistics

Standard deviation42.0984203
Coefficient of variation (CV)0.4786781481
Kurtosis-0.7896309292
Mean87.9472365
Median Absolute Deviation (MAD)20
Skewness0.7027982779
Sum7684038
Variance1772.276992
MonotonicityNot monotonic
2023-10-06T17:18:23.113010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 2046
 
2.3%
54 1951
 
2.2%
60 1897
 
2.1%
58 1875
 
2.1%
53 1830
 
2.1%
55 1829
 
2.1%
40 1809
 
2.0%
52 1804
 
2.0%
57 1787
 
2.0%
51 1765
 
2.0%
Other values (151) 68778
77.9%
ValueCountFrequency (%)
40 1809
2.0%
41 1413
1.6%
42 1345
1.5%
43 1319
1.5%
44 1320
1.5%
ValueCountFrequency (%)
200 137
0.2%
199 126
0.1%
198 98
0.1%
197 109
0.1%
196 118
0.1%

resprate_apache
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)0.1%
Missing1131
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean25.76998726
Minimum4
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:23.715580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q111
median28
Q336
95-th percentile53
Maximum60
Range56
Interquartile range (IQR)25

Descriptive statistics

Standard deviation15.10872605
Coefficient of variation (CV)0.5862915605
Kurtosis-0.9245303212
Mean25.76998726
Median Absolute Deviation (MAD)14
Skewness0.262306615
Sum2245931.7
Variance228.2736027
MonotonicityNot monotonic
2023-10-06T17:18:24.206355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 4188
 
4.7%
12 4102
 
4.6%
11 3786
 
4.3%
4 3417
 
3.9%
9 3329
 
3.8%
30 3042
 
3.4%
28 2988
 
3.4%
8 2845
 
3.2%
29 2809
 
3.2%
31 2642
 
3.0%
Other values (64) 54005
61.2%
ValueCountFrequency (%)
4 3417
3.9%
5 1995
2.3%
5.9 1
 
< 0.1%
6 2022
2.3%
7 2334
2.6%
ValueCountFrequency (%)
60 911
1.0%
59 646
0.7%
58 493
0.6%
57 488
0.6%
56 469
0.5%

sodium_apache
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)0.2%
Missing17644
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean137.948423
Minimum117
Maximum158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:24.592225image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum117
5-th percentile129
Q1135
median138
Q3141
95-th percentile146
Maximum158
Range41
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.292264907
Coefficient of variation (CV)0.03836408414
Kurtosis2.894688107
Mean137.948423
Median Absolute Deviation (MAD)3
Skewness-0.2941972751
Sum9744676.6
Variance28.00806784
MonotonicityNot monotonic
2023-10-06T17:18:24.884379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139 7262
8.2%
138 7181
8.1%
140 6710
 
7.6%
137 6509
 
7.4%
136 5575
 
6.3%
141 5415
 
6.1%
135 4338
 
4.9%
142 4179
 
4.7%
134 3569
 
4.0%
143 2746
 
3.1%
Other values (108) 17156
19.4%
(Missing) 17644
20.0%
ValueCountFrequency (%)
117 462
0.5%
118 59
 
0.1%
119 85
 
0.1%
120 81
 
0.1%
120.4 1
 
< 0.1%
ValueCountFrequency (%)
158 302
0.3%
157 55
 
0.1%
156 59
 
0.1%
155 98
 
0.1%
154 94
 
0.1%

temp_apache
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)0.2%
Missing3884
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean36.41382844
Minimum32.1
Maximum39.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:25.086251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32.1
5-th percentile35.3
Q136.2
median36.5
Q336.7
95-th percentile37.3
Maximum39.7
Range7.6
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.8343669531
Coefficient of variation (CV)0.02291346417
Kurtosis8.909963076
Mean36.41382844
Median Absolute Deviation (MAD)0.3
Skewness-0.9446889292
Sum3073327.12
Variance0.6961682124
MonotonicityNot monotonic
2023-10-06T17:18:25.398184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.4 8978
 
10.2%
36.6 8213
 
9.3%
36.7 7729
 
8.8%
36.3 6389
 
7.2%
36.5 5998
 
6.8%
36.8 5536
 
6.3%
36.2 4630
 
5.2%
36.1 4470
 
5.1%
36.9 3569
 
4.0%
36 2724
 
3.1%
Other values (180) 26164
29.6%
(Missing) 3884
 
4.4%
ValueCountFrequency (%)
32.1 488
0.6%
32.16 1
 
< 0.1%
32.2 62
 
0.1%
32.22 1
 
< 0.1%
32.27 1
 
< 0.1%
ValueCountFrequency (%)
39.7 359
0.4%
39.66 4
 
< 0.1%
39.61 5
 
< 0.1%
39.6 93
 
0.1%
39.55 9
 
< 0.1%

ventilated_apache
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.3271461187
Minimum0
Maximum1
Zeros58942
Zeros (%)66.8%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:25.600610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4691737936
Coefficient of variation (CV)1.434141403
Kurtosis-1.457069809
Mean0.3271461187
Median Absolute Deviation (MAD)0
Skewness0.7368605416
Sum28658
Variance0.2201240486
MonotonicityNot monotonic
2023-10-06T17:18:25.734512image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 58942
66.8%
1 28658
32.5%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 58942
66.8%
1 28658
32.5%
ValueCountFrequency (%)
1 28658
32.5%
0 58942
66.8%

wbc_apache
Real number (ℝ)

MISSING 

Distinct3064
Distinct (%)4.6%
Missing21063
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean12.15195222
Minimum0.9
Maximum45.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:25.907467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile4.3
Q17.5
median10.4
Q315.2
95-th percentile25.18
Maximum45.8
Range44.9
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation6.925786766
Coefficient of variation (CV)0.5699320276
Kurtosis4.163862629
Mean12.15195222
Median Absolute Deviation (MAD)3.54
Skewness1.668401
Sum816866.38
Variance47.96652233
MonotonicityNot monotonic
2023-10-06T17:18:26.225340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.4 521
 
0.6%
8 520
 
0.6%
7.6 511
 
0.6%
8.4 510
 
0.6%
8.8 510
 
0.6%
7.8 503
 
0.6%
8.2 494
 
0.6%
7.9 493
 
0.6%
7 485
 
0.5%
9 484
 
0.5%
Other values (3054) 62190
70.4%
(Missing) 21063
 
23.9%
ValueCountFrequency (%)
0.9 335
0.4%
0.92 1
 
< 0.1%
0.93 1
 
< 0.1%
0.94 1
 
< 0.1%
0.95 1
 
< 0.1%
ValueCountFrequency (%)
45.8 330
0.4%
45.7 2
 
< 0.1%
45.68 2
 
< 0.1%
45.5 2
 
< 0.1%
45.4 4
 
< 0.1%

d1_diasbp_max
Real number (ℝ)

Distinct120
Distinct (%)0.1%
Missing124
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean88.52186933
Minimum46
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:26.503445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q175
median86
Q399
95-th percentile125
Maximum165
Range119
Interquartile range (IQR)24

Descriptive statistics

Standard deviation19.83317481
Coefficient of variation (CV)0.2240483053
Kurtosis1.258596636
Mean88.52186933
Median Absolute Deviation (MAD)12
Skewness0.8173927883
Sum7804088
Variance393.3548229
MonotonicityNot monotonic
2023-10-06T17:18:26.795267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 2033
 
2.3%
80 2029
 
2.3%
82 1991
 
2.3%
88 1987
 
2.3%
86 1975
 
2.2%
83 1941
 
2.2%
78 1937
 
2.2%
87 1927
 
2.2%
90 1906
 
2.2%
85 1897
 
2.1%
Other values (110) 68537
77.6%
ValueCountFrequency (%)
46 416
0.5%
47 67
 
0.1%
48 119
 
0.1%
49 92
 
0.1%
50 160
 
0.2%
ValueCountFrequency (%)
165 398
0.5%
164 22
 
< 0.1%
163 24
 
< 0.1%
162 36
 
< 0.1%
161 26
 
< 0.1%

d1_diasbp_min
Real number (ℝ)

Distinct78
Distinct (%)0.1%
Missing124
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean50.11253403
Minimum13
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:27.089121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile29
Q142
median50
Q358
95-th percentile73
Maximum90
Range77
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.32574407
Coefficient of variation (CV)0.2659163886
Kurtosis0.3050388857
Mean50.11253403
Median Absolute Deviation (MAD)8
Skewness0.09658564163
Sum4417921
Variance177.5754551
MonotonicityNot monotonic
2023-10-06T17:18:27.359044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 3280
 
3.7%
51 2959
 
3.4%
52 2757
 
3.1%
46 2732
 
3.1%
55 2731
 
3.1%
53 2711
 
3.1%
49 2690
 
3.0%
47 2683
 
3.0%
48 2677
 
3.0%
45 2604
 
2.9%
Other values (68) 60336
68.3%
ValueCountFrequency (%)
13 513
0.6%
14 85
 
0.1%
15 120
 
0.1%
16 118
 
0.1%
17 139
 
0.2%
ValueCountFrequency (%)
90 406
0.5%
89 75
 
0.1%
88 84
 
0.1%
87 84
 
0.1%
86 83
 
0.1%

d1_diasbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)0.1%
Missing959
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean88.63663327
Minimum46
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:27.537892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q175
median87
Q399
95-th percentile125
Maximum165
Range119
Interquartile range (IQR)24

Descriptive statistics

Standard deviation19.82934181
Coefficient of variation (CV)0.2237149706
Kurtosis1.254733278
Mean88.63663327
Median Absolute Deviation (MAD)12
Skewness0.8138810728
Sum7740194
Variance393.2027966
MonotonicityNot monotonic
2023-10-06T17:18:27.717333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 2016
 
2.3%
80 2001
 
2.3%
88 1970
 
2.2%
82 1965
 
2.2%
86 1949
 
2.2%
83 1932
 
2.2%
87 1920
 
2.2%
78 1905
 
2.2%
90 1889
 
2.1%
85 1887
 
2.1%
Other values (110) 67891
76.9%
ValueCountFrequency (%)
46 411
0.5%
47 69
 
0.1%
48 117
 
0.1%
49 89
 
0.1%
50 159
 
0.2%
ValueCountFrequency (%)
165 397
0.4%
164 22
 
< 0.1%
163 24
 
< 0.1%
162 36
 
< 0.1%
161 26
 
< 0.1%

d1_diasbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)0.1%
Missing959
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean50.19420555
Minimum13
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:27.917245image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile29
Q142
median50
Q358
95-th percentile73
Maximum90
Range77
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.34863169
Coefficient of variation (CV)0.2659396945
Kurtosis0.2985945829
Mean50.19420555
Median Absolute Deviation (MAD)8
Skewness0.08885830992
Sum4383209
Variance178.185968
MonotonicityNot monotonic
2023-10-06T17:18:28.069843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 3247
 
3.7%
51 2930
 
3.3%
52 2736
 
3.1%
55 2718
 
3.1%
53 2700
 
3.1%
49 2673
 
3.0%
46 2660
 
3.0%
47 2656
 
3.0%
48 2638
 
3.0%
45 2577
 
2.9%
Other values (68) 59790
67.7%
ValueCountFrequency (%)
13 508
0.6%
14 83
 
0.1%
15 120
 
0.1%
16 117
 
0.1%
17 139
 
0.2%
ValueCountFrequency (%)
90 406
0.5%
89 75
 
0.1%
88 84
 
0.1%
87 83
 
0.1%
86 83
 
0.1%

d1_heartrate_max
Real number (ℝ)

Distinct120
Distinct (%)0.1%
Missing108
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean103.0245758
Minimum58
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:28.233940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile71
Q187
median101
Q3116
95-th percentile143
Maximum177
Range119
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.99554244
Coefficient of variation (CV)0.213498015
Kurtosis0.3357693892
Mean103.0245758
Median Absolute Deviation (MAD)14
Skewness0.572947649
Sum9084295
Variance483.8038871
MonotonicityNot monotonic
2023-10-06T17:18:28.385813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 1930
 
2.2%
100 1908
 
2.2%
90 1860
 
2.1%
98 1855
 
2.1%
92 1843
 
2.1%
94 1743
 
2.0%
88 1736
 
2.0%
102 1735
 
2.0%
104 1687
 
1.9%
106 1634
 
1.9%
Other values (110) 70245
79.6%
ValueCountFrequency (%)
58 599
0.7%
59 108
 
0.1%
60 196
 
0.2%
61 154
 
0.2%
62 222
 
0.3%
ValueCountFrequency (%)
177 425
0.5%
176 32
 
< 0.1%
175 30
 
< 0.1%
174 36
 
< 0.1%
173 31
 
< 0.1%

d1_heartrate_min
Real number (ℝ)

Distinct154
Distinct (%)0.2%
Missing108
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean70.40407821
Minimum0
Maximum175
Zeros533
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:28.604449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46
Q160
median70
Q381
95-th percentile99
Maximum175
Range175
Interquartile range (IQR)21

Descriptive statistics

Standard deviation17.0476138
Coefficient of variation (CV)0.2421395782
Kurtosis1.743502779
Mean70.40407821
Median Absolute Deviation (MAD)10
Skewness-0.08900130313
Sum6207950
Variance290.6211363
MonotonicityNot monotonic
2023-10-06T17:18:28.760422image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 3198
 
3.6%
70 2868
 
3.2%
68 2507
 
2.8%
62 2427
 
2.7%
66 2381
 
2.7%
64 2381
 
2.7%
72 2274
 
2.6%
74 2174
 
2.5%
65 2133
 
2.4%
58 2129
 
2.4%
Other values (144) 63704
72.2%
ValueCountFrequency (%)
0 533
0.6%
1 10
 
< 0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 6
 
< 0.1%
ValueCountFrequency (%)
175 1
< 0.1%
160 1
< 0.1%
155 1
< 0.1%
152 1
< 0.1%
150 2
< 0.1%

d1_mbp_max
Real number (ℝ)

Distinct125
Distinct (%)0.1%
Missing173
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean104.5012428
Minimum60
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:29.083927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile75
Q190
median102
Q3116
95-th percentile142
Maximum184
Range124
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.72809678
Coefficient of variation (CV)0.1983526343
Kurtosis1.144660935
Mean104.5012428
Median Absolute Deviation (MAD)13
Skewness0.8073580604
Sum9207709
Variance429.6539963
MonotonicityNot monotonic
2023-10-06T17:18:29.250407image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 1977
 
2.2%
100 1974
 
2.2%
98 1965
 
2.2%
97 1931
 
2.2%
103 1912
 
2.2%
104 1895
 
2.1%
102 1876
 
2.1%
95 1863
 
2.1%
94 1857
 
2.1%
101 1830
 
2.1%
Other values (115) 69031
78.2%
ValueCountFrequency (%)
60 400
0.5%
61 76
 
0.1%
62 97
 
0.1%
63 118
 
0.1%
64 114
 
0.1%
ValueCountFrequency (%)
184 414
0.5%
183 24
 
< 0.1%
182 23
 
< 0.1%
181 28
 
< 0.1%
180 28
 
< 0.1%

d1_mbp_min
Real number (ℝ)

Distinct91
Distinct (%)0.1%
Missing173
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean64.82363156
Minimum22
Maximum112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:29.384135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile40
Q155
median64
Q374
95-th percentile92
Maximum112
Range90
Interquartile range (IQR)19

Descriptive statistics

Standard deviation15.6695204
Coefficient of variation (CV)0.2417254328
Kurtosis0.3623843553
Mean64.82363156
Median Absolute Deviation (MAD)10
Skewness0.2133931462
Sum5711675
Variance245.5338694
MonotonicityNot monotonic
2023-10-06T17:18:29.558401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 2554
 
2.9%
61 2504
 
2.8%
64 2477
 
2.8%
62 2469
 
2.8%
59 2466
 
2.8%
63 2461
 
2.8%
65 2432
 
2.8%
67 2339
 
2.6%
56 2312
 
2.6%
58 2307
 
2.6%
Other values (81) 63790
72.3%
ValueCountFrequency (%)
22 520
0.6%
23 106
 
0.1%
24 93
 
0.1%
25 107
 
0.1%
26 115
 
0.1%
ValueCountFrequency (%)
112 492
0.6%
111 75
 
0.1%
110 69
 
0.1%
109 72
 
0.1%
108 87
 
0.1%

d1_mbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct122
Distinct (%)0.1%
Missing1333
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean104.4425021
Minimum60
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:29.733450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile75
Q190
median102
Q3116
95-th percentile142
Maximum181
Range121
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.62583012
Coefficient of variation (CV)0.1974850248
Kurtosis0.9510469497
Mean104.4425021
Median Absolute Deviation (MAD)13
Skewness0.7558018846
Sum9081380
Variance425.4248682
MonotonicityNot monotonic
2023-10-06T17:18:29.866776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 1944
 
2.2%
100 1930
 
2.2%
98 1924
 
2.2%
97 1906
 
2.2%
103 1897
 
2.1%
104 1869
 
2.1%
95 1833
 
2.1%
102 1828
 
2.1%
101 1811
 
2.1%
94 1805
 
2.0%
Other values (112) 68204
77.3%
ValueCountFrequency (%)
60 418
0.5%
61 74
 
0.1%
62 98
 
0.1%
63 117
 
0.1%
64 112
 
0.1%
ValueCountFrequency (%)
181 415
0.5%
180 27
 
< 0.1%
179 21
 
< 0.1%
178 31
 
< 0.1%
177 26
 
< 0.1%

d1_mbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct91
Distinct (%)0.1%
Missing1333
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean64.88922497
Minimum22
Maximum112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:30.100447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile40
Q155
median64
Q375
95-th percentile92
Maximum112
Range90
Interquartile range (IQR)20

Descriptive statistics

Standard deviation15.69078397
Coefficient of variation (CV)0.2418087746
Kurtosis0.3426589892
Mean64.88922497
Median Absolute Deviation (MAD)10
Skewness0.2036495539
Sum5642183
Variance246.2007017
MonotonicityNot monotonic
2023-10-06T17:18:30.253353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 2478
 
2.8%
61 2468
 
2.8%
63 2432
 
2.8%
59 2418
 
2.7%
64 2416
 
2.7%
62 2407
 
2.7%
65 2404
 
2.7%
67 2321
 
2.6%
57 2269
 
2.6%
56 2240
 
2.5%
Other values (81) 63098
71.5%
ValueCountFrequency (%)
22 501
0.6%
23 105
 
0.1%
24 94
 
0.1%
25 106
 
0.1%
26 116
 
0.1%
ValueCountFrequency (%)
112 477
0.5%
111 74
 
0.1%
110 65
 
0.1%
109 71
 
0.1%
108 89
 
0.1%

d1_resprate_max
Real number (ℝ)

Distinct79
Distinct (%)0.1%
Missing332
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean28.85162361
Minimum14
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:30.400901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile18
Q122
median26
Q332
95-th percentile48
Maximum92
Range78
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.68081415
Coefficient of variation (CV)0.3701980274
Kurtosis9.673778393
Mean28.85162361
Median Absolute Deviation (MAD)5
Skewness2.516234393
Sum2537558
Variance114.0797909
MonotonicityNot monotonic
2023-10-06T17:18:30.634356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 6094
 
6.9%
22 5460
 
6.2%
20 5211
 
5.9%
23 5138
 
5.8%
25 5137
 
5.8%
26 5114
 
5.8%
28 4802
 
5.4%
27 4386
 
5.0%
21 4057
 
4.6%
30 3880
 
4.4%
Other values (69) 38673
43.8%
ValueCountFrequency (%)
14 767
 
0.9%
15 450
 
0.5%
16 1018
 
1.2%
17 1099
1.2%
18 2573
2.9%
ValueCountFrequency (%)
92 470
0.5%
91 20
 
< 0.1%
90 19
 
< 0.1%
89 12
 
< 0.1%
88 26
 
< 0.1%

d1_resprate_min
Real number (ℝ)

ZEROS 

Distinct54
Distinct (%)0.1%
Missing332
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean12.8546821
Minimum0
Maximum100
Zeros3486
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:30.819484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q110
median13
Q316
95-th percentile21
Maximum100
Range100
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.054767861
Coefficient of variation (CV)0.3932238714
Kurtosis4.1597437
Mean12.8546821
Median Absolute Deviation (MAD)3
Skewness0.1672835358
Sum1130595
Variance25.55067813
MonotonicityNot monotonic
2023-10-06T17:18:31.134287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 10609
12.0%
14 8798
10.0%
13 7383
 
8.4%
16 7344
 
8.3%
10 7163
 
8.1%
11 7142
 
8.1%
15 6375
 
7.2%
9 4320
 
4.9%
18 3979
 
4.5%
17 3647
 
4.1%
Other values (44) 21192
24.0%
ValueCountFrequency (%)
0 3486
3.9%
1 217
 
0.2%
2 277
 
0.3%
3 324
 
0.4%
4 577
 
0.7%
ValueCountFrequency (%)
100 1
< 0.1%
96 1
< 0.1%
72 1
< 0.1%
69 1
< 0.1%
58 2
< 0.1%

d1_spo2_max
Real number (ℝ)

Distinct43
Distinct (%)< 0.1%
Missing280
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean99.24851143
Minimum0
Maximum100
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:31.333846image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile96
Q199
median100
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.758601514
Coefficient of variation (CV)0.01771917269
Kurtosis863.9552057
Mean99.24851143
Median Absolute Deviation (MAD)0
Skewness-18.86163112
Sum8734266
Variance3.092679284
MonotonicityNot monotonic
2023-10-06T17:18:31.467696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
100 58370
66.1%
99 12560
 
14.2%
98 8201
 
9.3%
97 4441
 
5.0%
96 2383
 
2.7%
95 1027
 
1.2%
94 463
 
0.5%
93 223
 
0.3%
92 122
 
0.1%
91 47
 
0.1%
Other values (33) 167
 
0.2%
(Missing) 280
 
0.3%
ValueCountFrequency (%)
0 5
< 0.1%
13 1
 
< 0.1%
16 2
 
< 0.1%
26 1
 
< 0.1%
31 1
 
< 0.1%
ValueCountFrequency (%)
100 58370
66.1%
99 12560
 
14.2%
98 8201
 
9.3%
97 4441
 
5.0%
96 2383
 
2.7%

d1_spo2_min
Real number (ℝ)

Distinct101
Distinct (%)0.1%
Missing280
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean90.49912504
Minimum0
Maximum100
Zeros130
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:31.767610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile77
Q189
median92
Q395
95-th percentile98
Maximum100
Range100
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.902782401
Coefficient of variation (CV)0.1094240679
Kurtosis31.70836799
Mean90.49912504
Median Absolute Deviation (MAD)3
Skewness-4.762192573
Sum7964285
Variance98.06509929
MonotonicityNot monotonic
2023-10-06T17:18:31.985551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94 8392
 
9.5%
92 8364
 
9.5%
93 8341
 
9.4%
95 7702
 
8.7%
91 6957
 
7.9%
96 6504
 
7.4%
90 6381
 
7.2%
97 5145
 
5.8%
89 3923
 
4.4%
98 3675
 
4.2%
Other values (91) 22620
25.6%
ValueCountFrequency (%)
0 130
0.1%
1 14
 
< 0.1%
2 29
 
< 0.1%
3 11
 
< 0.1%
4 12
 
< 0.1%
ValueCountFrequency (%)
100 1974
 
2.2%
99 2232
 
2.5%
98 3675
4.2%
97 5145
5.8%
96 6504
7.4%

d1_sysbp_max
Real number (ℝ)

Distinct143
Distinct (%)0.2%
Missing118
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean148.2610757
Minimum90
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:32.170466image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum90
5-th percentile111
Q1130
median146
Q3164
95-th percentile195
Maximum232
Range142
Interquartile range (IQR)34

Descriptive statistics

Standard deviation25.66585393
Coefficient of variation (CV)0.1731125571
Kurtosis0.2611815761
Mean148.2610757
Median Absolute Deviation (MAD)17
Skewness0.508058054
Sum13071586
Variance658.7360581
MonotonicityNot monotonic
2023-10-06T17:18:32.326405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 1538
 
1.7%
135 1449
 
1.6%
139 1432
 
1.6%
144 1429
 
1.6%
134 1428
 
1.6%
146 1419
 
1.6%
137 1416
 
1.6%
142 1409
 
1.6%
138 1408
 
1.6%
147 1398
 
1.6%
Other values (133) 73840
83.6%
ValueCountFrequency (%)
90 414
0.5%
91 54
 
0.1%
92 68
 
0.1%
93 55
 
0.1%
94 70
 
0.1%
ValueCountFrequency (%)
232 425
0.5%
231 23
 
< 0.1%
230 38
 
< 0.1%
229 21
 
< 0.1%
228 33
 
< 0.1%

d1_sysbp_min
Real number (ℝ)

Distinct120
Distinct (%)0.1%
Missing118
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean96.89450582
Minimum41
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:32.669612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile64
Q183
median96
Q3110
95-th percentile133
Maximum160
Range119
Interquartile range (IQR)27

Descriptive statistics

Standard deviation20.64911678
Coefficient of variation (CV)0.2131092636
Kurtosis0.3132040652
Mean96.89450582
Median Absolute Deviation (MAD)13
Skewness0.223775633
Sum8542801
Variance426.3860239
MonotonicityNot monotonic
2023-10-06T17:18:32.920948image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2093
 
2.4%
91 2065
 
2.3%
92 2035
 
2.3%
93 1931
 
2.2%
94 1920
 
2.2%
95 1868
 
2.1%
96 1865
 
2.1%
97 1822
 
2.1%
98 1742
 
2.0%
100 1729
 
2.0%
Other values (110) 69096
78.3%
ValueCountFrequency (%)
41 475
0.5%
42 45
 
0.1%
43 66
 
0.1%
44 63
 
0.1%
45 58
 
0.1%
ValueCountFrequency (%)
160 415
0.5%
159 39
 
< 0.1%
158 54
 
0.1%
157 40
 
< 0.1%
156 55
 
0.1%

d1_sysbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct143
Distinct (%)0.2%
Missing946
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean148.1529689
Minimum90
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:33.169094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum90
5-th percentile110
Q1130
median146
Q3164
95-th percentile195
Maximum232
Range142
Interquartile range (IQR)34

Descriptive statistics

Standard deviation25.72501437
Coefficient of variation (CV)0.1736381968
Kurtosis0.2536626007
Mean148.1529689
Median Absolute Deviation (MAD)17
Skewness0.505880323
Sum12939384
Variance661.7763644
MonotonicityNot monotonic
2023-10-06T17:18:33.368119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 1504
 
1.7%
135 1439
 
1.6%
139 1420
 
1.6%
144 1412
 
1.6%
137 1409
 
1.6%
134 1408
 
1.6%
146 1406
 
1.6%
142 1391
 
1.6%
147 1386
 
1.6%
145 1382
 
1.6%
Other values (133) 73181
82.9%
ValueCountFrequency (%)
90 430
0.5%
91 54
 
0.1%
92 67
 
0.1%
93 59
 
0.1%
94 72
 
0.1%
ValueCountFrequency (%)
232 417
0.5%
231 23
 
< 0.1%
230 37
 
< 0.1%
229 20
 
< 0.1%
228 33
 
< 0.1%

d1_sysbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)0.1%
Missing946
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean96.9650995
Minimum41.03
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:33.533765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum41.03
5-th percentile64
Q184
median96
Q3110
95-th percentile133
Maximum160
Range118.97
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.67583949
Coefficient of variation (CV)0.2132297043
Kurtosis0.3037326508
Mean96.9650995
Median Absolute Deviation (MAD)13
Skewness0.2220848547
Sum8468737.86
Variance427.4903387
MonotonicityNot monotonic
2023-10-06T17:18:33.670369image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2063
 
2.3%
91 2048
 
2.3%
92 2003
 
2.3%
93 1909
 
2.2%
94 1900
 
2.2%
95 1865
 
2.1%
96 1838
 
2.1%
97 1804
 
2.0%
98 1724
 
2.0%
99 1720
 
1.9%
Other values (110) 68464
77.5%
ValueCountFrequency (%)
41.03 462
0.5%
42 46
 
0.1%
43 66
 
0.1%
44 64
 
0.1%
45 57
 
0.1%
ValueCountFrequency (%)
160 414
0.5%
159 39
 
< 0.1%
158 53
 
0.1%
157 39
 
< 0.1%
156 55
 
0.1%

d1_temp_max
Real number (ℝ)

MISSING 

Distinct185
Distinct (%)0.2%
Missing2205
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean37.28514557
Minimum35.1
Maximum39.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:33.818798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35.1
5-th percentile36.4
Q136.9
median37.11
Q337.6
95-th percentile38.7
Maximum39.9
Range4.8
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.6940029103
Coefficient of variation (CV)0.01861338878
Kurtosis1.921436146
Mean37.28514557
Median Absolute Deviation (MAD)0.31
Skewness0.8546365614
Sum3209468.046
Variance0.4816400396
MonotonicityNot monotonic
2023-10-06T17:18:33.976483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1 7742
 
8.8%
36.9 7264
 
8.2%
36.8 6712
 
7.6%
37.2 6676
 
7.6%
37 5958
 
6.7%
36.7 4928
 
5.6%
37.3 4844
 
5.5%
37.4 4088
 
4.6%
37.6 3200
 
3.6%
36.6 3083
 
3.5%
Other values (175) 31584
35.8%
ValueCountFrequency (%)
35.1 518
0.6%
35.111 1
 
< 0.1%
35.2 31
 
< 0.1%
35.278 1
 
< 0.1%
35.3 32
 
< 0.1%
ValueCountFrequency (%)
39.9 335
0.4%
39.89208 1
 
< 0.1%
39.83652 1
 
< 0.1%
39.83 1
 
< 0.1%
39.8 96
 
0.1%

d1_temp_min
Real number (ℝ)

MISSING 

Distinct208
Distinct (%)0.2%
Missing2205
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean36.26720213
Minimum31.889
Maximum37.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:34.117442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum31.889
5-th percentile35.1
Q136.1
median36.4
Q336.61404
95-th percentile37.1
Maximum37.8
Range5.911
Interquartile range (IQR)0.51404

Descriptive statistics

Standard deviation0.7457118281
Coefficient of variation (CV)0.02056160344
Kurtosis12.42468226
Mean36.26720213
Median Absolute Deviation (MAD)0.3
Skewness-2.840046557
Sum3121844.493
Variance0.5560861306
MonotonicityNot monotonic
2023-10-06T17:18:34.283783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.4 10153
11.5%
36.6 8216
 
9.3%
36.3 7590
 
8.6%
36.7 7035
 
8.0%
36.5 6271
 
7.1%
36.2 5516
 
6.2%
36.1 5327
 
6.0%
36.8 4630
 
5.2%
36 3310
 
3.7%
36.9 2723
 
3.1%
Other values (198) 25308
28.7%
ValueCountFrequency (%)
31.889 500
0.6%
31.9 38
 
< 0.1%
31.944 1
 
< 0.1%
32 57
 
0.1%
32.05 1
 
< 0.1%
ValueCountFrequency (%)
37.8 356
0.4%
37.77 3
 
< 0.1%
37.72 1
 
< 0.1%
37.7 178
0.2%
37.66968 1
 
< 0.1%

h1_diasbp_max
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)0.1%
Missing3388
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean75.33131125
Minimum37
Maximum143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:34.500973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile49
Q162
median73
Q386
95-th percentile108
Maximum143
Range106
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.42224007
Coefficient of variation (CV)0.244549574
Kurtosis0.7897641655
Mean75.33131125
Median Absolute Deviation (MAD)12
Skewness0.6917760543
Sum6395327
Variance339.3789294
MonotonicityNot monotonic
2023-10-06T17:18:34.652975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 2052
 
2.3%
74 2047
 
2.3%
70 2005
 
2.3%
72 1951
 
2.2%
66 1948
 
2.2%
65 1903
 
2.2%
67 1866
 
2.1%
62 1852
 
2.1%
71 1845
 
2.1%
64 1835
 
2.1%
Other values (97) 65592
74.3%
(Missing) 3388
 
3.8%
ValueCountFrequency (%)
37 507
0.6%
38 135
 
0.2%
39 128
 
0.1%
40 174
 
0.2%
41 224
0.3%
ValueCountFrequency (%)
143 404
0.5%
142 26
 
< 0.1%
141 28
 
< 0.1%
140 29
 
< 0.1%
139 33
 
< 0.1%

h1_diasbp_min
Real number (ℝ)

MISSING 

Distinct92
Distinct (%)0.1%
Missing3388
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean62.83581087
Minimum22
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:34.800832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile38
Q152
median62
Q373
95-th percentile92
Maximum113
Range91
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.39371886
Coefficient of variation (CV)0.2608977052
Kurtosis0.1011734731
Mean62.83581087
Median Absolute Deviation (MAD)11
Skewness0.3045358066
Sum5334509
Variance268.7540181
MonotonicityNot monotonic
2023-10-06T17:18:35.200819image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 2317
 
2.6%
60 2289
 
2.6%
55 2241
 
2.5%
56 2201
 
2.5%
59 2146
 
2.4%
62 2130
 
2.4%
57 2072
 
2.3%
63 2062
 
2.3%
65 2023
 
2.3%
61 1999
 
2.3%
Other values (82) 63416
71.8%
(Missing) 3388
 
3.8%
ValueCountFrequency (%)
22 469
0.5%
23 69
 
0.1%
24 74
 
0.1%
25 93
 
0.1%
26 113
 
0.1%
ValueCountFrequency (%)
113 443
0.5%
112 53
 
0.1%
111 56
 
0.1%
110 76
 
0.1%
109 56
 
0.1%

h1_diasbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)0.1%
Missing6982
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean75.78303117
Minimum37
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:35.382761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile49
Q163
median74
Q387
95-th percentile109
Maximum144
Range107
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.49495946
Coefficient of variation (CV)0.2440514607
Kurtosis0.7938903378
Mean75.78303117
Median Absolute Deviation (MAD)12
Skewness0.6831747582
Sum6161312
Variance342.0635253
MonotonicityNot monotonic
2023-10-06T17:18:35.534323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 1953
 
2.2%
68 1934
 
2.2%
70 1898
 
2.1%
72 1842
 
2.1%
65 1812
 
2.1%
66 1802
 
2.0%
67 1782
 
2.0%
71 1775
 
2.0%
73 1747
 
2.0%
75 1733
 
2.0%
Other values (98) 63024
71.4%
(Missing) 6982
 
7.9%
ValueCountFrequency (%)
37 470
0.5%
38 123
 
0.1%
39 126
 
0.1%
40 153
 
0.2%
41 214
0.2%
ValueCountFrequency (%)
144 367
0.4%
143 34
 
< 0.1%
142 26
 
< 0.1%
141 28
 
< 0.1%
140 29
 
< 0.1%

h1_diasbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)0.1%
Missing6982
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean63.27006716
Minimum22
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:35.670545image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile38
Q152
median62
Q374
95-th percentile92
Maximum114
Range92
Interquartile range (IQR)22

Descriptive statistics

Standard deviation16.45114819
Coefficient of variation (CV)0.2600147104
Kurtosis0.1154244017
Mean63.27006716
Median Absolute Deviation (MAD)11
Skewness0.2854502616
Sum5143983
Variance270.6402767
MonotonicityNot monotonic
2023-10-06T17:18:35.860801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 2190
 
2.5%
60 2189
 
2.5%
55 2133
 
2.4%
56 2088
 
2.4%
59 2078
 
2.4%
62 2030
 
2.3%
57 1993
 
2.3%
63 1969
 
2.2%
65 1967
 
2.2%
61 1935
 
2.2%
Other values (83) 60730
68.8%
(Missing) 6982
 
7.9%
ValueCountFrequency (%)
22 457
0.5%
23 68
 
0.1%
24 69
 
0.1%
25 92
 
0.1%
26 111
 
0.1%
ValueCountFrequency (%)
114 399
0.5%
113 37
 
< 0.1%
112 54
 
0.1%
111 56
 
0.1%
110 75
 
0.1%

h1_heartrate_max
Real number (ℝ)

MISSING 

Distinct119
Distinct (%)0.1%
Missing2621
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean92.24184304
Minimum46
Maximum164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:36.017737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile61
Q177
median90
Q3106
95-th percentile132
Maximum164
Range118
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.8024706
Coefficient of variation (CV)0.2363620444
Kurtosis0.2545225687
Mean92.24184304
Median Absolute Deviation (MAD)14
Skewness0.5590305305
Sum7901713
Variance475.3477241
MonotonicityNot monotonic
2023-10-06T17:18:36.183567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 2210
 
2.5%
90 1841
 
2.1%
88 1816
 
2.1%
86 1778
 
2.0%
82 1775
 
2.0%
84 1769
 
2.0%
92 1700
 
1.9%
96 1668
 
1.9%
94 1570
 
1.8%
76 1566
 
1.8%
Other values (109) 67970
77.0%
(Missing) 2621
 
3.0%
ValueCountFrequency (%)
46 542
0.6%
47 72
 
0.1%
48 85
 
0.1%
49 86
 
0.1%
50 156
 
0.2%
ValueCountFrequency (%)
164 390
0.4%
163 37
 
< 0.1%
162 45
 
0.1%
161 38
 
< 0.1%
160 55
 
0.1%

h1_heartrate_min
Real number (ℝ)

MISSING 

Distinct109
Distinct (%)0.1%
Missing2621
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean83.72990673
Minimum36
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:36.384776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile54
Q169
median82
Q397
95-th percentile120
Maximum144
Range108
Interquartile range (IQR)28

Descriptive statistics

Standard deviation20.27599942
Coefficient of variation (CV)0.2421595845
Kurtosis-0.02730270332
Mean83.72990673
Median Absolute Deviation (MAD)14
Skewness0.390060726
Sum7172555
Variance411.1161525
MonotonicityNot monotonic
2023-10-06T17:18:36.534205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 2375
 
2.7%
70 2046
 
2.3%
84 1825
 
2.1%
74 1805
 
2.0%
78 1790
 
2.0%
82 1787
 
2.0%
76 1745
 
2.0%
72 1727
 
2.0%
90 1720
 
1.9%
60 1707
 
1.9%
Other values (99) 67136
76.0%
(Missing) 2621
 
3.0%
ValueCountFrequency (%)
36 548
0.6%
37 55
 
0.1%
38 67
 
0.1%
39 56
 
0.1%
40 97
 
0.1%
ValueCountFrequency (%)
144 441
0.5%
143 41
 
< 0.1%
142 58
 
0.1%
141 50
 
0.1%
140 97
 
0.1%

h1_mbp_max
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)0.1%
Missing4287
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean91.50018453
Minimum49
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:36.718283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile62
Q177
median89
Q3103
95-th percentile129
Maximum165
Range116
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.49113594
Coefficient of variation (CV)0.2239463893
Kurtosis0.6769282727
Mean91.50018453
Median Absolute Deviation (MAD)13
Skewness0.6743115002
Sum7685741
Variance419.8866523
MonotonicityNot monotonic
2023-10-06T17:18:36.934132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88 1794
 
2.0%
85 1727
 
2.0%
86 1725
 
2.0%
87 1703
 
1.9%
92 1693
 
1.9%
84 1687
 
1.9%
90 1683
 
1.9%
80 1682
 
1.9%
83 1674
 
1.9%
78 1672
 
1.9%
Other values (107) 66957
75.8%
(Missing) 4287
 
4.9%
ValueCountFrequency (%)
49 486
0.6%
50 103
 
0.1%
51 107
 
0.1%
52 148
 
0.2%
53 160
 
0.2%
ValueCountFrequency (%)
165 429
0.5%
164 19
 
< 0.1%
163 30
 
< 0.1%
162 20
 
< 0.1%
161 31
 
< 0.1%

h1_mbp_min
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)0.1%
Missing4287
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean79.3410717
Minimum32
Maximum138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:37.116080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile50
Q166
median78
Q392
95-th percentile113
Maximum138
Range106
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.12080083
Coefficient of variation (CV)0.2409949906
Kurtosis0.1176541243
Mean79.3410717
Median Absolute Deviation (MAD)13
Skewness0.3225702034
Sum6664412
Variance365.6050245
MonotonicityNot monotonic
2023-10-06T17:18:37.337424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 1909
 
2.2%
74 1875
 
2.1%
73 1810
 
2.1%
78 1792
 
2.0%
79 1776
 
2.0%
76 1764
 
2.0%
70 1755
 
2.0%
81 1726
 
2.0%
75 1720
 
1.9%
77 1717
 
1.9%
Other values (97) 66153
74.9%
(Missing) 4287
 
4.9%
ValueCountFrequency (%)
32 459
0.5%
33 52
 
0.1%
34 72
 
0.1%
35 62
 
0.1%
36 95
 
0.1%
ValueCountFrequency (%)
138 449
0.5%
137 43
 
< 0.1%
136 50
 
0.1%
135 60
 
0.1%
134 54
 
0.1%

h1_mbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)0.1%
Missing8455
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean91.48765486
Minimum49
Maximum163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:37.533975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile62
Q177
median89
Q3104
95-th percentile129
Maximum163
Range114
Interquartile range (IQR)27

Descriptive statistics

Standard deviation20.50773532
Coefficient of variation (CV)0.2241584982
Kurtosis0.5152203763
Mean91.48765486
Median Absolute Deviation (MAD)13
Skewness0.6295736112
Sum7303368
Variance420.567208
MonotonicityNot monotonic
2023-10-06T17:18:37.670416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88 1681
 
1.9%
85 1653
 
1.9%
86 1614
 
1.8%
87 1612
 
1.8%
79 1597
 
1.8%
92 1586
 
1.8%
93 1583
 
1.8%
83 1579
 
1.8%
89 1570
 
1.8%
91 1564
 
1.8%
Other values (105) 63790
72.3%
(Missing) 8455
 
9.6%
ValueCountFrequency (%)
49 485
0.5%
50 97
 
0.1%
51 109
 
0.1%
52 142
 
0.2%
53 158
 
0.2%
ValueCountFrequency (%)
163 380
0.4%
162 20
 
< 0.1%
161 32
 
< 0.1%
160 24
 
< 0.1%
159 34
 
< 0.1%

h1_mbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)0.1%
Missing8455
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean79.64713325
Minimum32
Maximum138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:37.884377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile50
Q166
median79
Q392
95-th percentile113
Maximum138
Range106
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.22481052
Coefficient of variation (CV)0.2413747957
Kurtosis0.1022839051
Mean79.64713325
Median Absolute Deviation (MAD)13
Skewness0.3029131362
Sum6358151
Variance369.5933394
MonotonicityNot monotonic
2023-10-06T17:18:38.055546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 1807
 
2.0%
74 1731
 
2.0%
73 1717
 
1.9%
79 1694
 
1.9%
78 1685
 
1.9%
81 1663
 
1.9%
75 1661
 
1.9%
77 1660
 
1.9%
76 1646
 
1.9%
71 1631
 
1.8%
Other values (97) 62934
71.3%
(Missing) 8455
 
9.6%
ValueCountFrequency (%)
32 439
0.5%
33 49
 
0.1%
34 72
 
0.1%
35 61
 
0.1%
36 93
 
0.1%
ValueCountFrequency (%)
138 442
0.5%
137 42
 
< 0.1%
136 50
 
0.1%
135 60
 
0.1%
134 54
 
0.1%

h1_resprate_max
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)0.1%
Missing4062
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean22.61559925
Minimum10
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:38.217502image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile14
Q118
median21
Q326
95-th percentile37
Maximum59
Range49
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.494508286
Coefficient of variation (CV)0.3313866771
Kurtosis3.805118711
Mean22.61559925
Median Absolute Deviation (MAD)4
Skewness1.525766062
Sum1904731
Variance56.16765445
MonotonicityNot monotonic
2023-10-06T17:18:38.383988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 7671
 
8.7%
18 7052
 
8.0%
16 5428
 
6.1%
22 5375
 
6.1%
21 5032
 
5.7%
19 4939
 
5.6%
24 4596
 
5.2%
17 4166
 
4.7%
23 4158
 
4.7%
25 3398
 
3.8%
Other values (40) 32407
36.7%
(Missing) 4062
 
4.6%
ValueCountFrequency (%)
10 754
 
0.9%
11 416
 
0.5%
12 1621
1.8%
13 1279
1.4%
14 2874
3.3%
ValueCountFrequency (%)
59 424
0.5%
58 30
 
< 0.1%
57 36
 
< 0.1%
56 37
 
< 0.1%
55 45
 
0.1%

h1_resprate_min
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)0.1%
Missing4062
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean17.2161668
Minimum0
Maximum189
Zeros614
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:38.566339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q114
median16
Q320
95-th percentile28
Maximum189
Range189
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.068978971
Coefficient of variation (CV)0.352516274
Kurtosis21.22326416
Mean17.2161668
Median Absolute Deviation (MAD)3
Skewness1.879758579
Sum1449980
Variance36.83250576
MonotonicityNot monotonic
2023-10-06T17:18:38.683857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 8732
 
9.9%
14 7566
 
8.6%
18 7168
 
8.1%
12 6500
 
7.4%
15 6305
 
7.1%
20 5607
 
6.4%
17 5269
 
6.0%
13 4570
 
5.2%
19 4093
 
4.6%
22 3068
 
3.5%
Other values (79) 25344
28.7%
(Missing) 4062
 
4.6%
ValueCountFrequency (%)
0 614
0.7%
1 39
 
< 0.1%
2 36
 
< 0.1%
3 57
 
0.1%
4 98
 
0.1%
ValueCountFrequency (%)
189 1
< 0.1%
129 1
< 0.1%
127 1
< 0.1%
125 1
< 0.1%
118 1
< 0.1%

h1_spo2_max
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)0.1%
Missing3925
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean98.051755
Minimum0
Maximum100
Zeros9
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:38.918834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile94
Q197
median99
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.174799636
Coefficient of variation (CV)0.03237881501
Kurtosis241.3892821
Mean98.051755
Median Absolute Deviation (MAD)1
Skewness-10.46435692
Sum8271548
Variance10.07935273
MonotonicityNot monotonic
2023-10-06T17:18:39.134059image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 34990
39.6%
99 12353
 
14.0%
98 10939
 
12.4%
97 8725
 
9.9%
96 6413
 
7.3%
95 4280
 
4.8%
94 2688
 
3.0%
93 1502
 
1.7%
92 955
 
1.1%
91 464
 
0.5%
Other values (62) 1050
 
1.2%
(Missing) 3925
 
4.4%
ValueCountFrequency (%)
0 9
< 0.1%
2 2
 
< 0.1%
10 2
 
< 0.1%
12 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
100 34990
39.6%
99 12353
 
14.0%
98 10939
 
12.4%
97 8725
 
9.9%
96 6413
 
7.3%

h1_spo2_min
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)0.1%
Missing3925
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean95.20124705
Minimum0
Maximum100
Zeros54
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:39.332781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile87
Q194
median96
Q399
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.551957317
Coefficient of variation (CV)0.06882217954
Kurtosis73.49753834
Mean95.20124705
Median Absolute Deviation (MAD)2
Skewness-6.716242641
Sum8031082
Variance42.92814468
MonotonicityNot monotonic
2023-10-06T17:18:39.517548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 13976
15.8%
97 9408
10.7%
98 9366
10.6%
96 9011
10.2%
99 8468
9.6%
95 7969
9.0%
94 6429
7.3%
93 5046
 
5.7%
92 3751
 
4.2%
91 2557
 
2.9%
Other values (90) 8378
9.5%
(Missing) 3925
 
4.4%
ValueCountFrequency (%)
0 54
0.1%
1 4
 
< 0.1%
2 13
 
< 0.1%
3 3
 
< 0.1%
4 4
 
< 0.1%
ValueCountFrequency (%)
100 13976
15.8%
99 8468
9.6%
98 9366
10.6%
97 9408
10.7%
96 9011
10.2%

h1_sysbp_max
Real number (ℝ)

MISSING 

Distinct149
Distinct (%)0.2%
Missing3379
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean133.1500501
Minimum75
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:39.700465image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile93
Q1113
median130
Q3150
95-th percentile183
Maximum223
Range148
Interquartile range (IQR)37

Descriptive statistics

Standard deviation27.49824617
Coefficient of variation (CV)0.2065207347
Kurtosis0.2399253317
Mean133.1500501
Median Absolute Deviation (MAD)18
Skewness0.5475137992
Sum11305105
Variance756.1535424
MonotonicityNot monotonic
2023-10-06T17:18:39.901372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
124 1306
 
1.5%
118 1303
 
1.5%
122 1294
 
1.5%
125 1281
 
1.5%
132 1258
 
1.4%
128 1253
 
1.4%
130 1246
 
1.4%
127 1244
 
1.4%
119 1236
 
1.4%
140 1231
 
1.4%
Other values (139) 72253
81.8%
(Missing) 3379
 
3.8%
ValueCountFrequency (%)
75 483
0.5%
76 62
 
0.1%
77 65
 
0.1%
78 84
 
0.1%
79 78
 
0.1%
ValueCountFrequency (%)
223 395
0.4%
222 37
 
< 0.1%
221 27
 
< 0.1%
220 35
 
< 0.1%
219 37
 
< 0.1%

h1_sysbp_min
Real number (ℝ)

MISSING 

Distinct142
Distinct (%)0.2%
Missing3379
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean116.3527001
Minimum53
Maximum194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:40.034117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile76
Q198
median115
Q3134
95-th percentile162
Maximum194
Range141
Interquartile range (IQR)36

Descriptive statistics

Standard deviation26.48710595
Coefficient of variation (CV)0.2276449617
Kurtosis-0.03894125347
Mean116.3527001
Median Absolute Deviation (MAD)18
Skewness0.2973993219
Sum9878926
Variance701.5667818
MonotonicityNot monotonic
2023-10-06T17:18:40.237562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110 1367
 
1.5%
106 1338
 
1.5%
112 1323
 
1.5%
118 1310
 
1.5%
115 1308
 
1.5%
114 1298
 
1.5%
102 1280
 
1.4%
104 1273
 
1.4%
105 1261
 
1.4%
113 1257
 
1.4%
Other values (132) 71890
81.4%
(Missing) 3379
 
3.8%
ValueCountFrequency (%)
53 473
0.5%
54 54
 
0.1%
55 58
 
0.1%
56 64
 
0.1%
57 70
 
0.1%
ValueCountFrequency (%)
194 467
0.5%
193 23
 
< 0.1%
192 41
 
< 0.1%
191 43
 
< 0.1%
190 56
 
0.1%

h1_sysbp_noninvasive_max
Real number (ℝ)

MISSING 

Distinct149
Distinct (%)0.2%
Missing6972
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean132.948138
Minimum75
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:40.384114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile93
Q1113
median130
Q3150
95-th percentile183
Maximum223
Range148
Interquartile range (IQR)37

Descriptive statistics

Standard deviation27.61734005
Coefficient of variation (CV)0.2077301755
Kurtosis0.2229232802
Mean132.948138
Median Absolute Deviation (MAD)18
Skewness0.549849434
Sum10810279
Variance762.7174712
MonotonicityNot monotonic
2023-10-06T17:18:40.517177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
118 1238
 
1.4%
122 1222
 
1.4%
125 1218
 
1.4%
124 1216
 
1.4%
119 1214
 
1.4%
127 1200
 
1.4%
128 1195
 
1.4%
117 1182
 
1.3%
123 1176
 
1.3%
132 1174
 
1.3%
Other values (139) 69277
78.5%
(Missing) 6972
 
7.9%
ValueCountFrequency (%)
75 472
0.5%
76 61
 
0.1%
77 66
 
0.1%
78 82
 
0.1%
79 77
 
0.1%
ValueCountFrequency (%)
223 370
0.4%
222 35
 
< 0.1%
221 25
 
< 0.1%
220 33
 
< 0.1%
219 37
 
< 0.1%

h1_sysbp_noninvasive_min
Real number (ℝ)

MISSING 

Distinct143
Distinct (%)0.2%
Missing6972
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean116.5380387
Minimum53
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:40.717680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile75
Q198
median115
Q3134
95-th percentile163
Maximum195
Range142
Interquartile range (IQR)36

Descriptive statistics

Standard deviation26.59818781
Coefficient of variation (CV)0.2282361031
Kurtosis-0.03502045867
Mean116.5380387
Median Absolute Deviation (MAD)18
Skewness0.2880032466
Sum9475941
Variance707.4635947
MonotonicityNot monotonic
2023-10-06T17:18:40.869620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110 1284
 
1.5%
115 1269
 
1.4%
106 1264
 
1.4%
112 1250
 
1.4%
118 1247
 
1.4%
114 1229
 
1.4%
119 1219
 
1.4%
105 1213
 
1.4%
102 1211
 
1.4%
111 1210
 
1.4%
Other values (133) 68916
78.1%
(Missing) 6972
 
7.9%
ValueCountFrequency (%)
53 468
0.5%
54 51
 
0.1%
55 57
 
0.1%
56 64
 
0.1%
57 70
 
0.1%
ValueCountFrequency (%)
195 432
0.5%
194 23
 
< 0.1%
193 22
 
< 0.1%
192 40
 
< 0.1%
191 43
 
< 0.1%

h1_temp_max
Real number (ℝ)

MISSING 

Distinct291
Distinct (%)0.4%
Missing20833
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean36.71098741
Minimum33.4
Maximum39.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:41.058435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum33.4
5-th percentile35.6
Q136.4
median36.7
Q337
95-th percentile37.9
Maximum39.5
Range6.1
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.754153705
Coefficient of variation (CV)0.02054299702
Kurtosis4.095983144
Mean36.71098741
Median Absolute Deviation (MAD)0.3
Skewness-0.2633156537
Sum2476192.811
Variance0.5687478108
MonotonicityNot monotonic
2023-10-06T17:18:41.200616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.7 6050
 
6.9%
36.8 5893
 
6.7%
36.6 5801
 
6.6%
36.4 4907
 
5.6%
36.9 4662
 
5.3%
36.5 3670
 
4.2%
37.1 3282
 
3.7%
37 3249
 
3.7%
36.3 3095
 
3.5%
37.2 2535
 
2.9%
Other values (281) 24307
27.5%
(Missing) 20833
23.6%
ValueCountFrequency (%)
33.4 380
0.4%
33.44444444 1
 
< 0.1%
33.47 1
 
< 0.1%
33.5 20
 
< 0.1%
33.6 29
 
< 0.1%
ValueCountFrequency (%)
39.5 275
0.3%
39.44 1
 
< 0.1%
39.4 94
 
0.1%
39.38 2
 
< 0.1%
39.33 1
 
< 0.1%

h1_temp_min
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)0.4%
Missing20833
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean36.6075503
Minimum32.9
Maximum39.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:41.358425image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum32.9
5-th percentile35.4
Q136.3
median36.6
Q336.94
95-th percentile37.8
Maximum39.3
Range6.4
Interquartile range (IQR)0.64

Descriptive statistics

Standard deviation0.7777137532
Coefficient of variation (CV)0.02124462705
Kurtosis4.883847596
Mean36.6075503
Median Absolute Deviation (MAD)0.3
Skewness-0.8013637509
Sum2469215.875
Variance0.604838682
MonotonicityNot monotonic
2023-10-06T17:18:41.519030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.7 5970
 
6.8%
36.6 5866
 
6.6%
36.8 5546
 
6.3%
36.4 5255
 
6.0%
36.9 4217
 
4.8%
36.5 3845
 
4.4%
36.3 3503
 
4.0%
37.1 2885
 
3.3%
37 2860
 
3.2%
36.2 2561
 
2.9%
Other values (291) 24943
28.3%
(Missing) 20833
23.6%
ValueCountFrequency (%)
32.9 365
0.4%
32.94 2
 
< 0.1%
33 34
 
< 0.1%
33.05 1
 
< 0.1%
33.09 1
 
< 0.1%
ValueCountFrequency (%)
39.3 260
0.3%
39.27 2
 
< 0.1%
39.22 1
 
< 0.1%
39.2 71
 
0.1%
39.16666667 1
 
< 0.1%

d1_bun_max
Real number (ℝ)

MISSING 

Distinct495
Distinct (%)0.6%
Missing9860
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean25.69169527
Minimum4
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:41.669883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7
Q113
median19
Q331
95-th percentile69
Maximum126
Range122
Interquartile range (IQR)18

Descriptive statistics

Standard deviation20.45157264
Coefficient of variation (CV)0.7960382692
Kurtosis5.430427749
Mean25.69169527
Median Absolute Deviation (MAD)8
Skewness2.132154069
Sum2014845.51
Variance418.2668233
MonotonicityNot monotonic
2023-10-06T17:18:42.184056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 3490
 
4.0%
15 3420
 
3.9%
13 3418
 
3.9%
12 3394
 
3.8%
11 3245
 
3.7%
16 3128
 
3.5%
10 3014
 
3.4%
17 2831
 
3.2%
18 2607
 
3.0%
9 2541
 
2.9%
Other values (485) 47336
53.6%
(Missing) 9860
 
11.2%
ValueCountFrequency (%)
4 796
0.9%
4.1 1
 
< 0.1%
4.3 2
 
< 0.1%
4.4 1
 
< 0.1%
4.6 2
 
< 0.1%
ValueCountFrequency (%)
126 383
0.4%
125 15
 
< 0.1%
124 13
 
< 0.1%
123 20
 
< 0.1%
122 15
 
< 0.1%

d1_bun_min
Real number (ℝ)

MISSING 

Distinct472
Distinct (%)0.6%
Missing9860
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean23.75745665
Minimum3
Maximum113.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:42.355362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q112
median18
Q329
95-th percentile63
Maximum113.09
Range110.09
Interquartile range (IQR)17

Descriptive statistics

Standard deviation18.76875779
Coefficient of variation (CV)0.7900154493
Kurtosis5.108485949
Mean23.75745665
Median Absolute Deviation (MAD)7
Skewness2.081018495
Sum1863154.78
Variance352.2662689
MonotonicityNot monotonic
2023-10-06T17:18:42.534010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 3734
 
4.2%
13 3627
 
4.1%
14 3513
 
4.0%
11 3464
 
3.9%
10 3412
 
3.9%
15 3369
 
3.8%
16 3118
 
3.5%
9 2926
 
3.3%
17 2807
 
3.2%
18 2614
 
3.0%
Other values (462) 45840
51.9%
(Missing) 9860
 
11.2%
ValueCountFrequency (%)
3 558
0.6%
3.1 2
 
< 0.1%
3.3 1
 
< 0.1%
3.4 2
 
< 0.1%
3.5 2
 
< 0.1%
ValueCountFrequency (%)
113.09 403
0.5%
113 17
 
< 0.1%
112 20
 
< 0.1%
111 21
 
< 0.1%
110 28
 
< 0.1%

d1_calcium_max
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)0.1%
Missing12315
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean8.38047888
Minimum6.2
Maximum10.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:42.700418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile7.1
Q17.9
median8.4
Q38.8
95-th percentile9.5
Maximum10.8
Range4.6
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.7367515816
Coefficient of variation (CV)0.08791282601
Kurtosis0.5762254348
Mean8.38047888
Median Absolute Deviation (MAD)0.5
Skewness-0.02673082477
Sum636656.6
Variance0.542802893
MonotonicityNot monotonic
2023-10-06T17:18:42.835068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
8.5 4497
 
5.1%
8.4 4487
 
5.1%
8.6 4359
 
4.9%
8.3 4298
 
4.9%
8.2 4164
 
4.7%
8.7 4045
 
4.6%
8.8 3902
 
4.4%
8.1 3869
 
4.4%
8.9 3533
 
4.0%
8 3533
 
4.0%
Other values (37) 35282
40.0%
(Missing) 12315
 
13.9%
ValueCountFrequency (%)
6.2 476
0.5%
6.3 87
 
0.1%
6.4 155
 
0.2%
6.5 191
0.2%
6.6 272
0.3%
ValueCountFrequency (%)
10.8 370
0.4%
10.7 51
 
0.1%
10.6 56
 
0.1%
10.5 90
 
0.1%
10.4 106
 
0.1%

d1_calcium_min
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)0.1%
Missing12315
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean8.1790454
Minimum5.5
Maximum10.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:42.984165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile6.8
Q17.7
median8.2
Q38.7
95-th percentile9.4
Maximum10.3
Range4.8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7854810439
Coefficient of variation (CV)0.0960357848
Kurtosis0.6109727832
Mean8.1790454
Median Absolute Deviation (MAD)0.5
Skewness-0.4148613766
Sum621353.9
Variance0.6169804704
MonotonicityNot monotonic
2023-10-06T17:18:43.118282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
8.4 4218
 
4.8%
8.3 4193
 
4.7%
8.5 4136
 
4.7%
8.2 4060
 
4.6%
8.1 3981
 
4.5%
8.6 3941
 
4.5%
8 3777
 
4.3%
8.7 3530
 
4.0%
7.9 3476
 
3.9%
8.8 3376
 
3.8%
Other values (39) 37281
42.2%
(Missing) 12315
 
13.9%
ValueCountFrequency (%)
5.5 370
0.4%
5.6 70
 
0.1%
5.7 81
 
0.1%
5.8 106
 
0.1%
5.9 112
 
0.1%
ValueCountFrequency (%)
10.3 377
0.4%
10.2 92
 
0.1%
10.1 128
 
0.1%
10 145
 
0.2%
9.9 200
0.2%

d1_creatinine_max
Real number (ℝ)

MISSING 

Distinct1182
Distinct (%)1.5%
Missing9561
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean1.48829896
Minimum0.34
Maximum11.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:43.267299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.34
5-th percentile0.52
Q10.76
median1
Q31.5
95-th percentile4.37
Maximum11.11
Range10.77
Interquartile range (IQR)0.74

Descriptive statistics

Standard deviation1.508419645
Coefficient of variation (CV)1.01351925
Kurtosis15.43917766
Mean1.48829896
Median Absolute Deviation (MAD)0.3
Skewness3.59316625
Sum117163.359
Variance2.275329824
MonotonicityNot monotonic
2023-10-06T17:18:43.500644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 2856
 
3.2%
0.7 2645
 
3.0%
0.9 2599
 
2.9%
1 2165
 
2.5%
0.6 1815
 
2.1%
1.1 1670
 
1.9%
1.2 1352
 
1.5%
1.3 1093
 
1.2%
0.5 984
 
1.1%
1.4 866
 
1.0%
Other values (1172) 60678
68.7%
(Missing) 9561
 
10.8%
ValueCountFrequency (%)
0.34 394
0.4%
0.344 1
 
< 0.1%
0.348 1
 
< 0.1%
0.35 38
 
< 0.1%
0.36 65
 
0.1%
ValueCountFrequency (%)
11.11 375
0.4%
11.1 4
 
< 0.1%
11.08 1
 
< 0.1%
11.07 1
 
< 0.1%
11.05 1
 
< 0.1%

d1_creatinine_min
Real number (ℝ)

MISSING 

Distinct1088
Distinct (%)1.4%
Missing9561
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean1.365745462
Minimum0.3
Maximum9.9379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:43.700480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.5
Q10.71
median0.94
Q31.4
95-th percentile3.87
Maximum9.9379
Range9.6379
Interquartile range (IQR)0.69

Descriptive statistics

Standard deviation1.335082834
Coefficient of variation (CV)0.9775487978
Kurtosis15.71505551
Mean1.365745462
Median Absolute Deviation (MAD)0.27
Skewness3.617185094
Sum107515.58
Variance1.782446175
MonotonicityNot monotonic
2023-10-06T17:18:43.884388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 2941
 
3.3%
0.7 2906
 
3.3%
0.9 2543
 
2.9%
0.6 2166
 
2.5%
1 2093
 
2.4%
1.1 1590
 
1.8%
0.5 1279
 
1.4%
1.2 1246
 
1.4%
1.3 980
 
1.1%
1.4 796
 
0.9%
Other values (1078) 60183
68.2%
(Missing) 9561
 
10.8%
ValueCountFrequency (%)
0.3 413
0.5%
0.31 49
 
0.1%
0.316 2
 
< 0.1%
0.32 47
 
0.1%
0.33 48
 
0.1%
ValueCountFrequency (%)
9.9379 390
0.4%
9.93 1
 
< 0.1%
9.92 2
 
< 0.1%
9.91 2
 
< 0.1%
9.9 5
 
< 0.1%

d1_glucose_max
Real number (ℝ)

MISSING 

Distinct537
Distinct (%)0.6%
Missing5458
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean174.8661773
Minimum73
Maximum611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:44.071750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile90
Q1117
median150
Q3201
95-th percentile351
Maximum611
Range538
Interquartile range (IQR)84

Descriptive statistics

Standard deviation86.80752419
Coefficient of variation (CV)0.4964226104
Kurtosis5.454519566
Mean174.8661773
Median Absolute Deviation (MAD)38
Skewness2.056432775
Sum14483466
Variance7535.546257
MonotonicityNot monotonic
2023-10-06T17:18:44.350693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112 727
 
0.8%
122 727
 
0.8%
113 719
 
0.8%
114 695
 
0.8%
107 695
 
0.8%
119 686
 
0.8%
110 683
 
0.8%
128 674
 
0.8%
109 670
 
0.8%
108 669
 
0.8%
Other values (527) 75881
86.0%
(Missing) 5458
 
6.2%
ValueCountFrequency (%)
73 425
0.5%
74 80
 
0.1%
75 92
 
0.1%
76 93
 
0.1%
77 112
 
0.1%
ValueCountFrequency (%)
611 413
0.5%
610 1
 
< 0.1%
609 2
 
< 0.1%
608 3
 
< 0.1%
607 3
 
< 0.1%

d1_glucose_min
Real number (ℝ)

MISSING 

Distinct256
Distinct (%)0.3%
Missing5458
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean114.3796151
Minimum33
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:44.500573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile66
Q191
median107
Q3131
95-th percentile186
Maximum288
Range255
Interquartile range (IQR)40

Descriptive statistics

Standard deviation38.27984556
Coefficient of variation (CV)0.33467367
Kurtosis3.394372378
Mean114.3796151
Median Absolute Deviation (MAD)19
Skewness1.379130656
Sum9473606
Variance1465.346576
MonotonicityNot monotonic
2023-10-06T17:18:44.684527image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97 1312
 
1.5%
96 1295
 
1.5%
92 1268
 
1.4%
95 1265
 
1.4%
98 1250
 
1.4%
102 1240
 
1.4%
100 1231
 
1.4%
104 1216
 
1.4%
99 1214
 
1.4%
91 1206
 
1.4%
Other values (246) 70329
79.7%
(Missing) 5458
 
6.2%
ValueCountFrequency (%)
33 448
0.5%
34 34
 
< 0.1%
35 38
 
< 0.1%
36 45
 
0.1%
37 31
 
< 0.1%
ValueCountFrequency (%)
288 402
0.5%
287 10
 
< 0.1%
286 11
 
< 0.1%
285 12
 
< 0.1%
284 6
 
< 0.1%

d1_hco3_max
Real number (ℝ)

MISSING 

Distinct219
Distinct (%)0.3%
Missing14390
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean24.33888949
Minimum12
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:44.843233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile17
Q122
median24
Q327
95-th percentile32
Maximum40
Range28
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.362206235
Coefficient of variation (CV)0.1792278254
Kurtosis1.149834089
Mean24.33888949
Median Absolute Deviation (MAD)3
Skewness0.2555051298
Sum1798497.9
Variance19.02884324
MonotonicityNot monotonic
2023-10-06T17:18:45.067853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 8112
9.2%
25 7759
8.8%
23 7368
8.3%
26 7044
8.0%
22 6080
 
6.9%
27 5602
 
6.3%
21 4760
 
5.4%
28 4246
 
4.8%
20 3642
 
4.1%
29 2772
 
3.1%
Other values (209) 16509
18.7%
(Missing) 14390
16.3%
ValueCountFrequency (%)
12 586
0.7%
12.1 1
 
< 0.1%
12.7 2
 
< 0.1%
13 265
0.3%
13.2 1
 
< 0.1%
ValueCountFrequency (%)
40 321
0.4%
39.3 1
 
< 0.1%
39 157
0.2%
38.9 1
 
< 0.1%
38.7 1
 
< 0.1%

d1_hco3_min
Real number (ℝ)

MISSING 

Distinct251
Distinct (%)0.3%
Missing14390
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean23.13571061
Minimum7
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:45.266176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile14
Q120.8
median23
Q326
95-th percentile31
Maximum39
Range32
Interquartile range (IQR)5.2

Descriptive statistics

Standard deviation4.984546276
Coefficient of variation (CV)0.2154481598
Kurtosis1.239008226
Mean23.13571061
Median Absolute Deviation (MAD)3
Skewness-0.26186757
Sum1709590.2
Variance24.84570158
MonotonicityNot monotonic
2023-10-06T17:18:45.417459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 7360
 
8.3%
24 7333
 
8.3%
25 6764
 
7.7%
22 6511
 
7.4%
26 5793
 
6.6%
21 5365
 
6.1%
27 4542
 
5.1%
20 4345
 
4.9%
28 3316
 
3.8%
19 3232
 
3.7%
Other values (241) 19333
21.9%
(Missing) 14390
16.3%
ValueCountFrequency (%)
7 599
0.7%
7.4 1
 
< 0.1%
7.7 1
 
< 0.1%
7.8 1
 
< 0.1%
7.9 1
 
< 0.1%
ValueCountFrequency (%)
39 336
0.4%
38.7 1
 
< 0.1%
38.2 1
 
< 0.1%
38.1 1
 
< 0.1%
38 153
0.2%

d1_hemaglobin_max
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)0.1%
Missing11519
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean11.44284895
Minimum6.8
Maximum17.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:45.600813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile8
Q19.8
median11.4
Q313
95-th percentile15.1
Maximum17.2
Range10.4
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.167426666
Coefficient of variation (CV)0.1894132025
Kurtosis-0.49932556
Mean11.44284895
Median Absolute Deviation (MAD)1.6
Skewness0.1548206774
Sum878410.3
Variance4.697738353
MonotonicityNot monotonic
2023-10-06T17:18:45.763436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.9 1368
 
1.5%
11.6 1352
 
1.5%
11.2 1336
 
1.5%
11.9 1296
 
1.5%
11.3 1281
 
1.5%
11.8 1280
 
1.4%
12.2 1263
 
1.4%
11.7 1258
 
1.4%
12.6 1251
 
1.4%
12.4 1232
 
1.4%
Other values (95) 63848
72.3%
(Missing) 11519
 
13.0%
ValueCountFrequency (%)
6.8 539
0.6%
6.9 67
 
0.1%
7 141
 
0.2%
7.1 156
 
0.2%
7.2 191
 
0.2%
ValueCountFrequency (%)
17.2 387
0.4%
17.1 63
 
0.1%
17 48
 
0.1%
16.9 60
 
0.1%
16.8 72
 
0.1%

d1_hemaglobin_min
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)0.1%
Missing11519
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean10.87801602
Minimum5.3
Maximum16.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:45.899305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.3
5-th percentile7
Q19.1
median10.9
Q312.6
95-th percentile14.7
Maximum16.7
Range11.4
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.357624936
Coefficient of variation (CV)0.2167329898
Kurtosis-0.5476711796
Mean10.87801602
Median Absolute Deviation (MAD)1.7
Skewness-0.005173484293
Sum835050.9
Variance5.558395339
MonotonicityNot monotonic
2023-10-06T17:18:46.034056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.9 1254
 
1.4%
11.6 1214
 
1.4%
11.1 1195
 
1.4%
11.2 1179
 
1.3%
11.8 1169
 
1.3%
10.2 1167
 
1.3%
11.3 1164
 
1.3%
12.2 1162
 
1.3%
12.1 1154
 
1.3%
11.9 1150
 
1.3%
Other values (105) 64957
73.6%
(Missing) 11519
 
13.0%
ValueCountFrequency (%)
5.3 489
0.6%
5.4 74
 
0.1%
5.5 60
 
0.1%
5.6 95
 
0.1%
5.7 82
 
0.1%
ValueCountFrequency (%)
16.7 372
0.4%
16.6 50
 
0.1%
16.5 53
 
0.1%
16.4 71
 
0.1%
16.3 80
 
0.1%

d1_hematocrit_max
Real number (ℝ)

MISSING 

Distinct312
Distinct (%)0.4%
Missing11051
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean34.50837854
Minimum20.4
Maximum51.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:46.186366image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.4
5-th percentile24.4
Q129.9
median34.5
Q338.9
95-th percentile44.8
Maximum51.5
Range31.1
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.239949188
Coefficient of variation (CV)0.1808241781
Kurtosis-0.4119875939
Mean34.50837854
Median Absolute Deviation (MAD)4.5
Skewness0.1125537924
Sum2665185.6
Variance38.93696587
MonotonicityNot monotonic
2023-10-06T17:18:46.319345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 639
 
0.7%
36 619
 
0.7%
38 595
 
0.7%
33 592
 
0.7%
37 551
 
0.6%
31 544
 
0.6%
34 540
 
0.6%
32 532
 
0.6%
39 505
 
0.6%
34.8 480
 
0.5%
Other values (302) 71636
81.1%
(Missing) 11051
 
12.5%
ValueCountFrequency (%)
20.4 451
0.5%
20.5 22
 
< 0.1%
20.6 23
 
< 0.1%
20.7 27
 
< 0.1%
20.8 29
 
< 0.1%
ValueCountFrequency (%)
51.5 382
0.4%
51.4 14
 
< 0.1%
51.3 21
 
< 0.1%
51.2 15
 
< 0.1%
51.1 12
 
< 0.1%

d1_hematocrit_min
Real number (ℝ)

MISSING 

Distinct340
Distinct (%)0.4%
Missing11051
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean32.91784082
Minimum16.1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:46.467445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum16.1
5-th percentile21.4
Q128
median33.2
Q337.9
95-th percentile43.8
Maximum50
Range33.9
Interquartile range (IQR)9.9

Descriptive statistics

Standard deviation6.852062795
Coefficient of variation (CV)0.208156508
Kurtosis-0.4748037806
Mean32.91784082
Median Absolute Deviation (MAD)5
Skewness-0.07200894052
Sum2542343.6
Variance46.95076454
MonotonicityNot monotonic
2023-10-06T17:18:46.600795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 570
 
0.6%
36 568
 
0.6%
31 555
 
0.6%
35 542
 
0.6%
29 534
 
0.6%
32 532
 
0.6%
33 517
 
0.6%
28 499
 
0.6%
30 492
 
0.6%
38 483
 
0.5%
Other values (330) 71941
81.5%
(Missing) 11051
 
12.5%
ValueCountFrequency (%)
16.1 424
0.5%
16.2 26
 
< 0.1%
16.3 18
 
< 0.1%
16.4 28
 
< 0.1%
16.5 24
 
< 0.1%
ValueCountFrequency (%)
50 393
0.4%
49.9 11
 
< 0.1%
49.8 18
 
< 0.1%
49.7 13
 
< 0.1%
49.6 13
 
< 0.1%

d1_platelets_max
Real number (ℝ)

MISSING 

Distinct559
Distinct (%)0.7%
Missing12767
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean207.0947998
Minimum27
Maximum585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:46.767449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile82
Q1148
median196
Q3252
95-th percentile369
Maximum585
Range558
Interquartile range (IQR)104

Descriptive statistics

Standard deviation89.65821642
Coefficient of variation (CV)0.4329332098
Kurtosis2.144262011
Mean207.0947998
Median Absolute Deviation (MAD)51
Skewness1.041941614
Sum15639178
Variance8038.595772
MonotonicityNot monotonic
2023-10-06T17:18:46.917080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182 458
 
0.5%
175 452
 
0.5%
176 451
 
0.5%
173 441
 
0.5%
181 435
 
0.5%
186 428
 
0.5%
178 426
 
0.5%
199 425
 
0.5%
180 422
 
0.5%
168 422
 
0.5%
Other values (549) 71157
80.6%
(Missing) 12767
 
14.5%
ValueCountFrequency (%)
27 392
0.4%
28 21
 
< 0.1%
29 29
 
< 0.1%
30 24
 
< 0.1%
31 37
 
< 0.1%
ValueCountFrequency (%)
585 377
0.4%
584 1
 
< 0.1%
583 1
 
< 0.1%
582 5
 
< 0.1%
581 3
 
< 0.1%

d1_platelets_min
Real number (ℝ)

MISSING 

Distinct540
Distinct (%)0.7%
Missing12767
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean196.6919243
Minimum18.55
Maximum557.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:47.050395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum18.55
5-th percentile71
Q1138
median187
Q3242
95-th percentile355
Maximum557.45
Range538.9
Interquartile range (IQR)104

Descriptive statistics

Standard deviation88.20666999
Coefficient of variation (CV)0.4484508975
Kurtosis1.801711135
Mean196.6919243
Median Absolute Deviation (MAD)52
Skewness0.9392693113
Sum14853584.05
Variance7780.416631
MonotonicityNot monotonic
2023-10-06T17:18:47.199417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
170 443
 
0.5%
176 443
 
0.5%
168 437
 
0.5%
173 436
 
0.5%
182 433
 
0.5%
161 427
 
0.5%
181 422
 
0.5%
175 419
 
0.5%
178 418
 
0.5%
186 418
 
0.5%
Other values (530) 71221
80.7%
(Missing) 12767
 
14.5%
ValueCountFrequency (%)
18.55 360
0.4%
19 33
 
< 0.1%
20 34
 
< 0.1%
21 34
 
< 0.1%
22 31
 
< 0.1%
ValueCountFrequency (%)
557.45 389
0.4%
557 4
 
< 0.1%
556 2
 
< 0.1%
555 7
 
< 0.1%
554 3
 
< 0.1%

d1_potassium_max
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)0.1%
Missing9053
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean4.252816701
Minimum2.8
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:47.334139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.8
5-th percentile3.3
Q13.8
median4.2
Q34.6
95-th percentile5.5
Maximum7
Range4.2
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.6676840555
Coefficient of variation (CV)0.1569980797
Kurtosis2.052167073
Mean4.252816701
Median Absolute Deviation (MAD)0.4
Skewness1.041824544
Sum336954.92
Variance0.4458019979
MonotonicityNot monotonic
2023-10-06T17:18:47.555529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 6045
 
6.8%
4.1 6043
 
6.8%
4.2 5820
 
6.6%
3.9 5545
 
6.3%
4.3 5125
 
5.8%
3.8 5082
 
5.8%
4.4 4696
 
5.3%
4.5 4076
 
4.6%
3.7 4052
 
4.6%
4.6 3489
 
4.0%
Other values (90) 29258
33.1%
(Missing) 9053
 
10.3%
ValueCountFrequency (%)
2.8 486
0.6%
2.9 226
 
0.3%
3 390
 
0.4%
3.1 633
0.7%
3.2 998
1.1%
ValueCountFrequency (%)
7 357
0.4%
6.9 75
 
0.1%
6.8 91
 
0.1%
6.7 114
 
0.1%
6.6 91
 
0.1%

d1_potassium_min
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)0.1%
Missing9053
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean3.934218046
Minimum2.4
Maximum5.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:47.751494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.4
5-th percentile3
Q13.6
median3.9
Q34.3
95-th percentile5
Maximum5.8
Range3.4
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.5800730665
Coefficient of variation (CV)0.1474430394
Kurtosis0.4532535659
Mean3.934218046
Median Absolute Deviation (MAD)0.4
Skewness0.2679740026
Sum311712.03
Variance0.3364847625
MonotonicityNot monotonic
2023-10-06T17:18:47.937074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.9 6152
 
7.0%
3.8 6068
 
6.9%
4 5927
 
6.7%
3.7 5598
 
6.3%
4.1 5423
 
6.1%
4.2 4949
 
5.6%
3.6 4935
 
5.6%
3.5 4297
 
4.9%
4.3 4029
 
4.6%
3.4 3619
 
4.1%
Other values (106) 28234
32.0%
(Missing) 9053
 
10.3%
ValueCountFrequency (%)
2.4 550
0.6%
2.5 221
0.3%
2.6 305
0.3%
2.7 442
0.5%
2.72 1
 
< 0.1%
ValueCountFrequency (%)
5.8 349
0.4%
5.7 152
0.2%
5.6 198
0.2%
5.58 1
 
< 0.1%
5.5 247
0.3%

d1_sodium_max
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)0.1%
Missing9554
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean139.1184237
Minimum123
Maximum158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:48.137841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum123
5-th percentile131
Q1136
median139
Q3142
95-th percentile147
Maximum158
Range35
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.825883123
Coefficient of variation (CV)0.03468902963
Kurtosis1.912433021
Mean139.1184237
Median Absolute Deviation (MAD)3
Skewness0.05196396269
Sum10952793.5
Variance23.28914792
MonotonicityNot monotonic
2023-10-06T17:18:48.269267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139 8171
9.3%
140 8108
9.2%
138 7561
8.6%
141 7135
 
8.1%
137 6524
 
7.4%
142 5978
 
6.8%
136 5214
 
5.9%
143 4331
 
4.9%
135 3764
 
4.3%
144 3306
 
3.7%
Other values (61) 18638
21.1%
(Missing) 9554
10.8%
ValueCountFrequency (%)
123 562
0.6%
124 132
 
0.1%
125 159
 
0.2%
126 216
 
0.2%
127 309
0.4%
ValueCountFrequency (%)
158 328
0.4%
157 65
 
0.1%
156 77
 
0.1%
155 105
 
0.1%
154 111
 
0.1%

d1_sodium_min
Real number (ℝ)

MISSING 

Distinct138
Distinct (%)0.2%
Missing9554
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean137.7026534
Minimum117
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:48.400706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum117
5-th percentile129
Q1135
median138
Q3141
95-th percentile145
Maximum153
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.936003476
Coefficient of variation (CV)0.03584537665
Kurtosis2.626072567
Mean137.7026534
Median Absolute Deviation (MAD)3
Skewness-0.74967781
Sum10841329.9
Variance24.36413032
MonotonicityNot monotonic
2023-10-06T17:18:48.587635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139 8088
9.2%
138 8064
9.1%
137 7455
8.4%
140 7387
 
8.4%
136 6374
 
7.2%
141 5960
 
6.8%
135 4940
 
5.6%
142 4682
 
5.3%
134 4143
 
4.7%
143 3159
 
3.6%
Other values (128) 18478
20.9%
(Missing) 9554
10.8%
ValueCountFrequency (%)
117 516
0.6%
118 66
 
0.1%
119 84
 
0.1%
120 92
 
0.1%
120.4 1
 
< 0.1%
ValueCountFrequency (%)
153 322
0.4%
152 116
 
0.1%
151 121
 
0.1%
150.7 1
 
< 0.1%
150 194
0.2%

d1_wbc_max
Real number (ℝ)

MISSING 

Distinct3087
Distinct (%)4.1%
Missing12501
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean12.49869588
Minimum1.2
Maximum46.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:48.803669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile4.79
Q18
median11
Q315.22
95-th percentile25.3
Maximum46.08
Range44.88
Interquartile range (IQR)7.22

Descriptive statistics

Standard deviation6.805731342
Coefficient of variation (CV)0.5445153163
Kurtosis4.518887468
Mean12.49869588
Median Absolute Deviation (MAD)3.44
Skewness1.719596057
Sum947188.67
Variance46.31797909
MonotonicityNot monotonic
2023-10-06T17:18:49.033850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.2 550
 
0.6%
8.4 542
 
0.6%
8.6 541
 
0.6%
9 532
 
0.6%
8.8 530
 
0.6%
8 529
 
0.6%
9.2 524
 
0.6%
7.2 521
 
0.6%
7.8 518
 
0.6%
9.6 512
 
0.6%
Other values (3077) 70484
79.8%
(Missing) 12501
 
14.2%
ValueCountFrequency (%)
1.2 387
0.4%
1.21 1
 
< 0.1%
1.23 1
 
< 0.1%
1.24 2
 
< 0.1%
1.28 1
 
< 0.1%
ValueCountFrequency (%)
46.08 383
0.4%
46 1
 
< 0.1%
45.9 3
 
< 0.1%
45.8 2
 
< 0.1%
45.77 1
 
< 0.1%

d1_wbc_min
Real number (ℝ)

MISSING 

Distinct2766
Distinct (%)3.6%
Missing12501
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean11.32823024
Minimum0.9
Maximum40.898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:49.199355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile4.34
Q17.4
median10.1
Q313.8
95-th percentile22.479
Maximum40.898
Range39.998
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation5.958047286
Coefficient of variation (CV)0.5259468745
Kurtosis4.659508248
Mean11.32823024
Median Absolute Deviation (MAD)3
Skewness1.699033441
Sum858487.272
Variance35.49832746
MonotonicityNot monotonic
2023-10-06T17:18:49.336718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.8 609
 
0.7%
8 605
 
0.7%
7.6 601
 
0.7%
7.2 598
 
0.7%
8.4 597
 
0.7%
7.8 588
 
0.7%
7.4 585
 
0.7%
8.6 582
 
0.7%
9 576
 
0.7%
8.3 574
 
0.7%
Other values (2756) 69868
79.1%
(Missing) 12501
 
14.2%
ValueCountFrequency (%)
0.9 371
0.4%
0.92 1
 
< 0.1%
0.94 1
 
< 0.1%
0.95 2
 
< 0.1%
0.97 2
 
< 0.1%
ValueCountFrequency (%)
40.898 384
0.4%
40.89 1
 
< 0.1%
40.8 5
 
< 0.1%
40.76 1
 
< 0.1%
40.67 1
 
< 0.1%

apache_4a_hospital_death_prob
Real number (ℝ)

MISSING  ZEROS 

Distinct101
Distinct (%)0.1%
Missing7594
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean0.0884336349
Minimum-1
Maximum0.99
Zeros2352
Zeros (%)2.7%
Negative2195
Negative (%)2.5%
Memory size1.3 MiB
2023-10-06T17:18:49.501121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10.02
median0.05
Q30.13
95-th percentile0.5
Maximum0.99
Range1.99
Interquartile range (IQR)0.11

Descriptive statistics

Standard deviation0.2449520638
Coefficient of variation (CV)2.769897043
Kurtosis9.979727382
Mean0.0884336349
Median Absolute Deviation (MAD)0.04
Skewness-1.458679765
Sum7135.71
Variance0.06000151355
MonotonicityNot monotonic
2023-10-06T17:18:49.683831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 10556
 
12.0%
0.02 9572
 
10.8%
0.03 7234
 
8.2%
0.04 5765
 
6.5%
0.05 4700
 
5.3%
0.06 3708
 
4.2%
0.07 3145
 
3.6%
0.08 2713
 
3.1%
0 2352
 
2.7%
0.09 2321
 
2.6%
Other values (91) 28624
32.4%
(Missing) 7594
 
8.6%
ValueCountFrequency (%)
-1 2195
 
2.5%
0 2352
 
2.7%
0.01 10556
12.0%
0.02 9572
10.8%
0.03 7234
8.2%
ValueCountFrequency (%)
0.99 1
 
< 0.1%
0.98 4
 
< 0.1%
0.97 11
< 0.1%
0.96 18
< 0.1%
0.95 20
< 0.1%

apache_4a_icu_death_prob
Real number (ℝ)

MISSING  ZEROS 

Distinct99
Distinct (%)0.1%
Missing7594
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean0.04524302888
Minimum-1
Maximum0.97
Zeros9258
Zeros (%)10.5%
Negative2066
Negative (%)2.3%
Memory size1.3 MiB
2023-10-06T17:18:49.870363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10.01
median0.02
Q30.06
95-th percentile0.35
Maximum0.97
Range1.97
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.2146834118
Coefficient of variation (CV)4.745115815
Kurtosis14.13212006
Mean0.04524302888
Median Absolute Deviation (MAD)0.02
Skewness-2.012146733
Sum3650.66
Variance0.04608896732
MonotonicityNot monotonic
2023-10-06T17:18:50.017442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 20234
22.9%
0.02 11308
12.8%
0 9258
10.5%
0.03 7029
 
8.0%
0.04 4896
 
5.5%
0.05 3568
 
4.0%
0.06 2691
 
3.0%
0.07 2066
 
2.3%
-1 2066
 
2.3%
0.08 1706
 
1.9%
Other values (89) 15868
18.0%
(Missing) 7594
 
8.6%
ValueCountFrequency (%)
-1 2066
 
2.3%
0 9258
10.5%
0.01 20234
22.9%
0.02 11308
12.8%
0.03 7029
 
8.0%
ValueCountFrequency (%)
0.97 3
 
< 0.1%
0.96 3
 
< 0.1%
0.95 6
 
< 0.1%
0.94 11
< 0.1%
0.93 15
< 0.1%

aids
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.0008675799087
Minimum0
Maximum1
Zeros87524
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:50.534776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02944209757
Coefficient of variation (CV)33.93589141
Kurtosis1147.698023
Mean0.0008675799087
Median Absolute Deviation (MAD)0
Skewness33.90681081
Sum76
Variance0.0008668371092
MonotonicityNot monotonic
2023-10-06T17:18:50.684286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 87524
99.1%
1 76
 
0.1%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 87524
99.1%
1 76
 
0.1%
ValueCountFrequency (%)
1 76
 
0.1%
0 87524
99.1%

cirrhosis
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.01574200913
Minimum0
Maximum1
Zeros86221
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:50.783983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.124476404
Coefficient of variation (CV)7.907275556
Kurtosis58.54369672
Mean0.01574200913
Median Absolute Deviation (MAD)0
Skewness7.780897128
Sum1379
Variance0.01549437516
MonotonicityNot monotonic
2023-10-06T17:18:50.866878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 86221
97.7%
1 1379
 
1.6%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 86221
97.7%
1 1379
 
1.6%
ValueCountFrequency (%)
1 1379
 
1.6%
0 86221
97.7%

diabetes_mellitus
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.2253310502
Minimum0
Maximum1
Zeros67861
Zeros (%)76.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:50.965272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4178025379
Coefficient of variation (CV)1.854172062
Kurtosis-0.271158204
Mean0.2253310502
Median Absolute Deviation (MAD)0
Skewness1.314856641
Sum19739
Variance0.1745589607
MonotonicityNot monotonic
2023-10-06T17:18:51.084154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 67861
76.9%
1 19739
 
22.4%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 67861
76.9%
1 19739
 
22.4%
ValueCountFrequency (%)
1 19739
 
22.4%
0 67861
76.9%

hepatic_failure
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.01307077626
Minimum0
Maximum1
Zeros86455
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:51.217272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1135785117
Coefficient of variation (CV)8.689500111
Kurtosis71.52394495
Mean0.01307077626
Median Absolute Deviation (MAD)0
Skewness8.574515262
Sum1145
Variance0.01290007832
MonotonicityNot monotonic
2023-10-06T17:18:51.356050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 86455
97.9%
1 1145
 
1.3%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 86455
97.9%
1 1145
 
1.3%
ValueCountFrequency (%)
1 1145
 
1.3%
0 86455
97.9%

immunosuppression
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.02607305936
Minimum0
Maximum1
Zeros85316
Zeros (%)96.6%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:51.450361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1593535215
Coefficient of variation (CV)6.111807567
Kurtosis33.38251024
Mean0.02607305936
Median Absolute Deviation (MAD)0
Skewness5.948255886
Sum2284
Variance0.02539354482
MonotonicityNot monotonic
2023-10-06T17:18:51.567078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 85316
96.6%
1 2284
 
2.6%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 85316
96.6%
1 2284
 
2.6%
ValueCountFrequency (%)
1 2284
 
2.6%
0 85316
96.6%

leukemia
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.007123287671
Minimum0
Maximum1
Zeros86976
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:51.682741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08409891308
Coefficient of variation (CV)11.80619357
Kurtosis135.3995864
Mean0.007123287671
Median Absolute Deviation (MAD)0
Skewness11.72162511
Sum624
Variance0.007072627182
MonotonicityNot monotonic
2023-10-06T17:18:51.767612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 86976
98.5%
1 624
 
0.7%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 86976
98.5%
1 624
 
0.7%
ValueCountFrequency (%)
1 624
 
0.7%
0 86976
98.5%

lymphoma
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.004223744292
Minimum0
Maximum1
Zeros87230
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:51.850522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06485331364
Coefficient of variation (CV)15.3544602
Kurtosis231.7742958
Mean0.004223744292
Median Absolute Deviation (MAD)0
Skewness15.28950634
Sum370
Variance0.00420595229
MonotonicityNot monotonic
2023-10-06T17:18:51.933904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 87230
98.8%
1 370
 
0.4%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 87230
98.8%
1 370
 
0.4%
ValueCountFrequency (%)
1 370
 
0.4%
0 87230
98.8%

solid_tumor_with_metastasis
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing684
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.02060502283
Minimum0
Maximum1
Zeros85795
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2023-10-06T17:18:52.020250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1420587422
Coefficient of variation (CV)6.894374414
Kurtosis43.55544897
Mean0.02060502283
Median Absolute Deviation (MAD)0
Skewness6.749404015
Sum1805
Variance0.02018068624
MonotonicityNot monotonic
2023-10-06T17:18:52.134081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 85795
97.2%
1 1805
 
2.0%
(Missing) 684
 
0.8%
ValueCountFrequency (%)
0 85795
97.2%
1 1805
 
2.0%
ValueCountFrequency (%)
1 1805
 
2.0%
0 85795
97.2%

apache_3j_bodysystem
Text

MISSING 

Distinct11
Distinct (%)< 0.1%
Missing1566
Missing (%)1.8%
Memory size1.3 MiB
2023-10-06T17:18:52.282725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length16
Mean length11.78091054
Min length6

Characters and Unicode

Total characters1021617
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSepsis
2nd rowRespiratory
3rd rowMetabolic
4th rowCardiovascular
5th rowNeurological
ValueCountFrequency (%)
cardiovascular 28833
33.2%
neurological 11415
 
13.2%
sepsis 11368
 
13.1%
respiratory 11236
 
13.0%
gastrointestinal 8711
 
10.0%
metabolic 7339
 
8.5%
trauma 3680
 
4.2%
genitourinary 2085
 
2.4%
musculoskeletal/skin 1128
 
1.3%
hematological 621
 
0.7%
2023-10-06T17:18:52.584234image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 146028
14.3%
r 108114
10.6%
i 93834
9.2%
o 84008
 
8.2%
s 82483
 
8.1%
l 72943
 
7.1%
e 55333
 
5.4%
c 49940
 
4.9%
t 48542
 
4.8%
u 48269
 
4.7%
Other values (18) 232123
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 932643
91.3%
Uppercase Letter 87846
 
8.6%
Other Punctuation 1128
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 146028
15.7%
r 108114
11.6%
i 93834
10.1%
o 84008
9.0%
s 82483
8.8%
l 72943
7.8%
e 55333
 
5.9%
c 49940
 
5.4%
t 48542
 
5.2%
u 48269
 
5.2%
Other values (9) 143149
15.3%
Uppercase Letter
ValueCountFrequency (%)
C 28833
32.8%
S 12496
14.2%
N 11415
 
13.0%
R 11236
 
12.8%
G 11098
 
12.6%
M 8467
 
9.6%
T 3680
 
4.2%
H 621
 
0.7%
Other Punctuation
ValueCountFrequency (%)
/ 1128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1020489
99.9%
Common 1128
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 146028
14.3%
r 108114
10.6%
i 93834
9.2%
o 84008
 
8.2%
s 82483
 
8.1%
l 72943
 
7.1%
e 55333
 
5.4%
c 49940
 
4.9%
t 48542
 
4.8%
u 48269
 
4.7%
Other values (17) 230995
22.6%
Common
ValueCountFrequency (%)
/ 1128
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1021617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 146028
14.3%
r 108114
10.6%
i 93834
9.2%
o 84008
 
8.2%
s 82483
 
8.1%
l 72943
 
7.1%
e 55333
 
5.4%
c 49940
 
4.9%
t 48542
 
4.8%
u 48269
 
4.7%
Other values (18) 232123
22.7%

apache_2_bodysystem
Text

MISSING 

Distinct10
Distinct (%)< 0.1%
Missing1566
Missing (%)1.8%
Memory size1.3 MiB
2023-10-06T17:18:52.734337image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.87528541
Min length6

Characters and Unicode

Total characters1116519
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCardiovascular
2nd rowRespiratory
3rd rowMetabolic
4th rowCardiovascular
5th rowNeurologic
ValueCountFrequency (%)
cardiovascular 37358
41.2%
neurologic 11415
 
12.6%
respiratory 11236
 
12.4%
gastrointestinal 8711
 
9.6%
metabolic 7339
 
8.1%
undefined 3995
 
4.4%
diagnoses 3995
 
4.4%
trauma 3680
 
4.1%
renal/genitourinary 2363
 
2.6%
haematologic 621
 
0.7%
2023-10-06T17:18:53.050795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 165394
14.8%
r 125720
11.3%
i 98107
 
8.8%
o 95074
 
8.5%
s 74006
 
6.6%
l 67807
 
6.1%
c 56733
 
5.1%
e 56033
 
5.0%
u 54816
 
4.9%
d 49013
 
4.4%
Other values (20) 273816
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1020750
91.4%
Uppercase Letter 89411
 
8.0%
Space Separator 3995
 
0.4%
Other Punctuation 2363
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 165394
16.2%
r 125720
12.3%
i 98107
9.6%
o 95074
9.3%
s 74006
7.3%
l 67807
 
6.6%
c 56733
 
5.6%
e 56033
 
5.5%
u 54816
 
5.4%
d 49013
 
4.8%
Other values (9) 178047
17.4%
Uppercase Letter
ValueCountFrequency (%)
C 37358
41.8%
R 13599
 
15.2%
N 11415
 
12.8%
G 11074
 
12.4%
M 7339
 
8.2%
U 3995
 
4.5%
T 3680
 
4.1%
H 621
 
0.7%
D 330
 
0.4%
Space Separator
ValueCountFrequency (%)
3995
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1110161
99.4%
Common 6358
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 165394
14.9%
r 125720
11.3%
i 98107
 
8.8%
o 95074
 
8.6%
s 74006
 
6.7%
l 67807
 
6.1%
c 56733
 
5.1%
e 56033
 
5.0%
u 54816
 
4.9%
d 49013
 
4.4%
Other values (18) 267458
24.1%
Common
ValueCountFrequency (%)
3995
62.8%
/ 2363
37.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1116519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 165394
14.8%
r 125720
11.3%
i 98107
 
8.8%
o 95074
 
8.5%
s 74006
 
6.6%
l 67807
 
6.1%
c 56733
 
5.1%
e 56033
 
5.0%
u 54816
 
4.9%
d 49013
 
4.4%
Other values (20) 273816
24.5%